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graph

Aggregated news, research, and updates specifically regarding graph. Auto-curated by our AI Engine.

business #gpu 📝 BlogAnalyzed: Jan 18, 2026 07:45

AMD's Commitment: Affordable GPUs for Everyone!

Published:Jan 18, 2026 07:43

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1 min read

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cnBeta

Analysis

AMD's promise to keep GPU prices accessible is fantastic news for the tech community! This commitment ensures that cutting-edge technology remains within reach, fostering innovation and wider adoption of AI-driven applications. This is a win for both consumers and the future of AI development!

Key Takeaways

•AMD is actively working to make GPUs more accessible.
•This commitment will benefit consumers and the AI industry.
•The focus is on ensuring affordability during potential component shortages.

Reference

“AMD is dedicated to making sure GPUs remain affordable.”

Permalink cnBeta

product #image generation 📝 BlogAnalyzed: Jan 17, 2026 06:17

AI Photography Reaches New Heights: Capturing Realistic Editorial Portraits

Published:Jan 17, 2026 06:11

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1 min read

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r/Bard

Analysis

This is a fantastic demonstration of AI's growing capabilities in image generation! The focus on realistic lighting and textures is particularly impressive, producing a truly modern and captivating editorial feel. It's exciting to see AI advancing so rapidly in the realm of visual arts.

Key Takeaways

•AI is now capable of generating high-end lifestyle portraits with impressive realism.
•The focus is on achieving a natural look, prioritizing lighting, textures, and subtle details.
•This showcases AI's potential in creative fields, particularly photography and editorial work.

Reference

“The goal was to keep it minimal and realistic — soft shadows, refined textures, and a casual pose that feels unforced.”

Permalink r/Bard

business #llm 📝 BlogAnalyzed: Jan 16, 2026 19:47

AI Engineer Seeks New Opportunities: Building the Future with LLMs

Published:Jan 16, 2026 19:43

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1 min read

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r/mlops

Analysis

This full-stack AI/ML engineer is ready to revolutionize the tech landscape! With expertise in cutting-edge technologies like LangGraph and RAG, they're building impressive AI-powered applications, including multi-agent systems and sophisticated chatbots. Their experience promises innovative solutions for businesses and exciting advancements in the field.

Key Takeaways

Reference

“I’m a Full-Stack AI/ML Engineer with strong experience building LLM-powered applications, multi-agent systems, and scalable Python backends.”

Permalink r/mlops

product #gpu 📝 BlogAnalyzed: Jan 16, 2026 16:32

AMD Unleashes FSR Redstone: A Glimpse into the Future of Graphics!

Published:Jan 16, 2026 16:23

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1 min read

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Toms Hardware

Analysis

AMD's FSR Redstone press roundtable at CES 2026 promises an exciting look at the evolution of graphics technology! This is a fantastic opportunity to hear directly from AMD about their innovations and how they plan to revolutionize the visual experience. The roundtable offers valuable insights into the direction of their future products.

Key Takeaways

•AMD is showcasing its latest advancements in graphics, including FSR Redstone.
•The roundtable offers a deep dive into AMD's future plans for visual technologies.
•Learn about the innovative technologies powering next-generation gaming and visual experiences.

Reference

“We attend a roundtable interview with AMD to discuss their graphics technologies like FSR Redstone, and more at CES 2026.”

Permalink Toms Hardware

product #agent 📝 BlogAnalyzed: Jan 16, 2026 20:30

Amp Free: Revolutionizing Coding with Free AI Assistance

Published:Jan 16, 2026 16:22

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1 min read

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Zenn AI

Analysis

Amp Free is a game-changer! This innovative AI coding agent, powered by cutting-edge models like Claude Opus 4.5 and GPT-5.1, offers coding assistance, refactoring, and bug fixes completely free of charge. This is a fantastic step towards making powerful AI tools accessible to everyone.

Key Takeaways

•Amp Free provides free AI coding assistance via advertising.
•It uses state-of-the-art AI models like Claude Opus 4.5 and GPT-5.1.
•Features include coding assistance, refactoring, and bug fixing.

Reference

“Amp Free leverages advertising to make AI coding assistance accessible.”

Permalink Zenn AI

research #agent 📝 BlogAnalyzed: Jan 15, 2026 08:30

Agentic RAG: Navigating Complex Queries with Autonomous AI

Published:Jan 15, 2026 04:48

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1 min read

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Zenn AI

Analysis

The article's focus on Agentic RAG using LangGraph offers a practical glimpse into building more sophisticated Retrieval-Augmented Generation (RAG) systems. However, the analysis would benefit from detailing the specific advantages of an agentic approach over traditional RAG, such as improved handling of multi-step queries or reasoning capabilities, to showcase its core value proposition. The brief code snippet provides a starting point, but a more in-depth discussion of agent design and optimization would increase the piece's utility.

Key Takeaways

•Agentic RAG aims to improve information retrieval using autonomous AI agents.
•The article showcases an implementation example using LangGraph.
•The article is a summary of a longer, more in-depth blog post.

Reference

“The article is a summary and technical extract from a blog post at https://agenticai-flow.com/posts/agentic-rag-advanced-retrieval/”

Permalink Zenn AI

ethics #ai video 📝 BlogAnalyzed: Jan 15, 2026 07:32

AI-Generated Pornography: A Future Trend?

Published:Jan 14, 2026 19:00

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1 min read

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r/ArtificialInteligence

Analysis

The article highlights the potential of AI in generating pornographic content. The discussion touches on user preferences and the potential displacement of human-produced content. This trend raises ethical concerns and significant questions about copyright and content moderation within the AI industry.

Key Takeaways

•The article originates from a Reddit discussion within the r/ArtificialInteligence subreddit.
•The core question revolves around the future of AI-generated pornographic videos and their potential impact.
•It implicitly touches on issues of content creation, user preference, and industry disruption.

Reference

“I'm wondering when, or if, they will have access for people to create full videos with prompts to create anything they wish to see?”

Permalink r/ArtificialInteligence

product #image generation 📝 BlogAnalyzed: Jan 15, 2026 07:01

Transforming Corporate Photography: Using Gemini to Create Stylized Visuals for Internal Documents

Published:Jan 14, 2026 10:08

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1 min read

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Zenn Gemini

Analysis

This article highlights a practical application of AI image generation, specifically addressing the common problem of lacking suitable visual assets for internal documents. It leverages Gemini's capabilities for style transfer, demonstrating its potential for enhancing productivity and content creation within organizations. However, the article's focus on a niche application might limit its broader appeal, and lacks deeper discussion on the technical aspects and limitations of the tool.

Key Takeaways

•The article showcases a practical use case of AI image generation for solving a common internal document creation challenge.
•It leverages Gemini to transform existing corporate photos into a specific artistic style (e.g., Makoto Shinkai), improving visual appeal.
•The article is a two-part series, indicating a more in-depth exploration of the topic and related design elements.

Reference

“Suddenly, when creating internal materials or presentation documents, don't you ever feel troubled by the lack of 'good-looking photos of the company'?”

Permalink Zenn Gemini

policy #security 📝 BlogAnalyzed: Jan 10, 2026 06:00

IETF Daily (2026-01-08): Accelerating PQC Implementation and the Emergence of an AI Trust Framework

Published:Jan 10, 2026 05:49

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1 min read

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Qiita AI

Analysis

This article summarizes IETF activity, specifically focusing on post-quantum cryptography (PQC) implementation and developments in AI trust frameworks. The focus on standardization efforts in these areas suggests a growing awareness of the need for secure and reliable AI systems. Further context is needed to determine the specific advancements and their potential impact.

Key Takeaways

•Reports on IETF activities related to AI.
•Highlights progress in Post-Quantum Cryptography (PQC) implementation.
•Covers the emergence of AI trust frameworks.

Reference

“"日刊IETFは、I-D AnnounceやIETF Announceに投稿されたメールをサマリーし続けるという修行的な活動です！！"”

Permalink Qiita AI

Computer Vision #Image Steganography/Data Hiding 📝 BlogAnalyzed: Jan 16, 2026 01:51

Embedding Textual Information in Images Using Quinary Pixel Combinations

Published:Jan 16, 2026 01:51

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1 min read

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Analysis

The article's title suggests a technical paper. The use of "quinary pixel combinations" implies a novel approach to steganography or data hiding within images. Further analysis of the content is needed to understand the method's effectiveness, efficiency, and potential applications.

Key Takeaways

Reference

“”

Permalink

Medical AI #Photoplethysmography, Tissue Analysis, AI, Machine Learning 📝 BlogAnalyzed: Jan 16, 2026 01:52

Inferring Optical Tissue Properties from Photoplethysmography using Hybrid Amortized Inference

Published:Jan 16, 2026 01:52

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1 min read

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Analysis

The article title suggests a technical paper exploring the use of AI, specifically hybrid amortized inference, to analyze photoplethysmography (PPG) data for medical applications, potentially related to tissue analysis. This is likely an academic or research-oriented piece, originating from Apple ML, which indicates the source is Apple's Machine Learning research division.

Key Takeaways

Reference

“The article likely details a novel method for extracting information about tissue properties using a combination of PPG and a specific AI technique. It suggests a potential advancement in non-invasive medical diagnostics.”

Permalink

research #health 📝 BlogAnalyzed: Jan 10, 2026 05:00

SleepFM Clinical: AI Model Predicts 130+ Diseases from Single Night's Sleep

Published:Jan 8, 2026 15:22

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1 min read

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MarkTechPost

Analysis

The development of SleepFM Clinical represents a significant advancement in leveraging multimodal data for predictive healthcare. The open-source release of the code could accelerate research and adoption, although the generalizability of the model across diverse populations will be a key factor in its clinical utility. Further validation and rigorous clinical trials are needed to assess its real-world effectiveness and address potential biases.

Key Takeaways

•SleepFM Clinical is a multimodal AI model.
•It predicts over 130 diseases.
•It's based on a single night of polysomnography.

Reference

“A team of Stanford Medicine researchers have introduced SleepFM Clinical, a multimodal sleep foundation model that learns from clinical polysomnography and predicts long term disease risk from a single night of sleep.”

Permalink MarkTechPost

research #agent 📝 BlogAnalyzed: Jan 10, 2026 05:39

Building Sophisticated Agentic AI: LangGraph, OpenAI, and Advanced Reasoning Techniques

Published:Jan 6, 2026 20:44

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1 min read

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MarkTechPost

Analysis

The article highlights a practical application of LangGraph in constructing more complex agentic systems, moving beyond simple loop architectures. The integration of adaptive deliberation and memory graphs suggests a focus on improving agent reasoning and knowledge retention, potentially leading to more robust and reliable AI solutions. A crucial assessment point will be the scalability and generalizability of this architecture to diverse real-world tasks.

Key Takeaways

•The system utilizes LangGraph for orchestrating agentic workflows.
•Adaptive deliberation allows the agent to choose between fast and deep reasoning.
•A Zettelkasten-style memory graph stores and links atomic knowledge.

Reference

“In this tutorial, we build a genuinely advanced Agentic AI system using LangGraph and OpenAI models by going beyond simple planner, executor loops.”

Permalink MarkTechPost

research #llm 🔬 ResearchAnalyzed: Jan 6, 2026 07:20

CogCanvas: A Promising Training-Free Approach to Long-Context LLM Memory

Published:Jan 6, 2026 05:00

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1 min read

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ArXiv AI

Analysis

CogCanvas presents a compelling training-free alternative for managing long LLM conversations by extracting and organizing cognitive artifacts. The significant performance gains over RAG and GraphRAG, particularly in temporal reasoning, suggest a valuable contribution to addressing context window limitations. However, the comparison to heavily-optimized, training-dependent approaches like EverMemOS highlights the potential for further improvement through fine-tuning.

Key Takeaways

•CogCanvas is a training-free framework for managing long LLM conversations.
•It outperforms RAG and GraphRAG, especially in temporal reasoning tasks.
•It extracts and organizes cognitive artifacts into a temporal-aware graph.

Reference

“We introduce CogCanvas, a training-free framework that extracts verbatim-grounded cognitive artifacts (decisions, facts, reminders) from conversation turns and organizes them into a temporal-aware graph for compression-resistant retrieval.”

Permalink ArXiv AI

research #llm 🔬 ResearchAnalyzed: Jan 6, 2026 07:21

HyperJoin: LLM-Enhanced Hypergraph Approach to Joinable Table Discovery

Published:Jan 6, 2026 05:00

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1 min read

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ArXiv NLP

Analysis

This paper introduces a novel approach to joinable table discovery by leveraging LLMs and hypergraphs to capture complex relationships between tables and columns. The proposed HyperJoin framework addresses limitations of existing methods by incorporating both intra-table and inter-table structural information, potentially leading to more coherent and accurate join results. The use of a hierarchical interaction network and coherence-aware reranking module are key innovations.

Key Takeaways

•HyperJoin uses a hypergraph to model tables and their relationships.
•It employs a Hierarchical Interaction Network (HIN) for column representation learning.
•A coherence-aware reranking module improves the consistency of join results.

Reference

“To address these limitations, we propose HyperJoin, a large language model (LLM)-augmented Hypergraph framework for Joinable table discovery.”

Permalink ArXiv NLP

research #gpu 📝 BlogAnalyzed: Jan 6, 2026 07:23

ik_llama.cpp Achieves 3-4x Speedup in Multi-GPU LLM Inference

Published:Jan 5, 2026 17:37

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1 min read

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r/LocalLLaMA

Analysis

This performance breakthrough in llama.cpp significantly lowers the barrier to entry for local LLM experimentation and deployment. The ability to effectively utilize multiple lower-cost GPUs offers a compelling alternative to expensive, high-end cards, potentially democratizing access to powerful AI models. Further investigation is needed to understand the scalability and stability of this "split mode graph" execution mode across various hardware configurations and model sizes.

Key Takeaways

•ik_llama.cpp achieves 3-4x speed improvement in multi-GPU LLM inference.
•New "split mode graph" enables simultaneous and maximum utilization of multiple GPUs.
•This breakthrough reduces the need for expensive high-end GPUs for local LLM deployment.

Reference

“the ik_llama.cpp project (a performance-optimized fork of llama.cpp) achieved a breakthrough in local LLM inference for multi-GPU configurations, delivering a massive performance leap — not just a marginal gain, but a 3x to 4x speed improvement.”

Permalink r/LocalLLaMA

research #llm 🔬 ResearchAnalyzed: Jan 5, 2026 08:34

MetaJuLS: Meta-RL for Scalable, Green Structured Inference in LLMs

Published:Jan 5, 2026 05:00

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1 min read

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ArXiv NLP

Analysis

This paper presents a compelling approach to address the computational bottleneck of structured inference in LLMs. The use of meta-reinforcement learning to learn universal constraint propagation policies is a significant step towards efficient and generalizable solutions. The reported speedups and cross-domain adaptation capabilities are promising for real-world deployment.

Key Takeaways

•MetaJuLS uses meta-RL for universal constraint propagation in LLMs.
•It achieves 1.5-2x speedups over GPU baselines with minimal accuracy loss.
•The policy adapts to new languages/tasks in seconds, not hours.

Reference

“By reducing propagation steps in LLM deployments, MetaJuLS contributes to Green AI by directly reducing inference carbon footprint.”

Permalink ArXiv NLP

research #cryptography 📝 BlogAnalyzed: Jan 4, 2026 15:21

ChatGPT Explores Code-Based CSPRNG Construction

Published:Jan 4, 2026 07:57

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1 min read

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Qiita ChatGPT

Analysis

This article, seemingly generated by or about ChatGPT, discusses the construction of cryptographically secure pseudorandom number generators (CSPRNGs) using code-based one-way functions. The exploration of such advanced cryptographic primitives highlights the potential of AI in contributing to security research, but the actual novelty and rigor of the approach require further scrutiny. The reliance on code-based cryptography suggests a focus on post-quantum security considerations.

Key Takeaways

•The article discusses CSPRNG construction using code-based cryptography.
•It highlights the potential of AI in cryptographic research.
•The approach may be relevant to post-quantum cryptography.

Reference

“疑似乱数生成器（Pseudorandom Generator, PRG）は暗号の中核的構成要素であり、暗号化、署名、鍵生成など、ほぼすべての暗号技術に利用され...”

Permalink Qiita ChatGPT

research #gnn 📝 BlogAnalyzed: Jan 3, 2026 14:21

MeshGraphNets for Physics Simulation: A Deep Dive

Published:Jan 3, 2026 14:06

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1 min read

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Qiita ML

Analysis

This article introduces MeshGraphNets, highlighting their application in physics simulations. A deeper analysis would benefit from discussing the computational cost and scalability compared to traditional methods. Furthermore, exploring the limitations and potential biases introduced by the graph-based representation would enhance the critique.

Key Takeaways

•MeshGraphNets (MGN) were proposed by DeepMind in 2020.
•MGNs are a type of Graph Neural Network (GNN).
•MGNs are used in various fields, including physics simulation.

Reference

“近年、Graph Neural Network（GNN）は推薦・化学・知識グラフなど様々な分野で使われていますが、2020年に DeepMind が提案した MeshGraphNets（MGN）は、その中でも特に”

Permalink Qiita ML

Research #Graph Partitioning 🔬 ResearchAnalyzed: Jan 10, 2026 07:07

Optimizing Airline Alliance Strategies Using AI-Driven Graph Partitioning

Published:Dec 30, 2025 23:45

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1 min read

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ArXiv

Analysis

This ArXiv paper explores a novel application of AI, specifically multi-attribute graph partitioning, to optimize airline alliance strategies. The research potentially offers valuable insights for airlines seeking to enhance competitiveness and expand market reach through strategic partnerships.

Key Takeaways

•Applies AI to the complex domain of airline alliance optimization.
•Utilizes multi-attribute graph partitioning as the core analytical method.
•Aims to maximize competition and market penetration for airlines.

Reference

“The study analyzes airline alliances through multi-attribute graph partitioning.”

Permalink ArXiv

Research #Algorithms 🔬 ResearchAnalyzed: Jan 10, 2026 07:07

New Algorithms Advance Global Minimum Vertex-Cut in Directed Graphs

Published:Dec 30, 2025 17:06

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1 min read

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ArXiv

Analysis

This ArXiv article presents advancements in algorithms for the global minimum vertex-cut problem within directed graphs. The research likely explores computational complexity and efficiency improvements for network flow and related graph theory applications.

Key Takeaways

•The research focuses on the global minimum vertex-cut problem.
•The work pertains to directed graphs.
•It likely contributes to improved computational efficiency in graph algorithms.

Reference

“The context is from ArXiv, indicating a research paper.”

Permalink ArXiv

Research #Graph Analytics 🔬 ResearchAnalyzed: Jan 10, 2026 07:08

Boosting Graph Analytics on Trusted Processors with Oblivious Memory

Published:Dec 30, 2025 14:28

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1 min read

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ArXiv

Analysis

This ArXiv article explores the potential of oblivious memory techniques to improve the performance of graph analytics on trusted processors. The research likely focuses on enhancing security and privacy while maintaining computational efficiency for graph-based data analysis.

Key Takeaways

•Investigates the application of oblivious memory for secure graph analytics.
•Focuses on improving performance on trusted processor environments.
•Aims to enhance both security and efficiency in graph data analysis.

Reference

“The article is sourced from ArXiv, indicating a pre-print research paper.”

Permalink ArXiv

Research #Agent 🔬 ResearchAnalyzed: Jan 10, 2026 07:11

AI-Powered Root Cause Analysis for Cloud Application Incidents

Published:Dec 26, 2025 18:56

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1 min read

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ArXiv

Analysis

This research explores using agentic systems and graph traversal to automate and improve root cause analysis of code-related incidents in cloud applications. The approach, if successful, could significantly reduce incident resolution time and improve system reliability.

Key Takeaways

•Applies agentic systems to automatically analyze code-related incidents.
•Utilizes structured graph traversal for efficient incident diagnosis.
•Aims to improve incident resolution time and system reliability in cloud environments.

Reference

“The research focuses on root cause analysis of code-related incidents in cloud applications.”

Permalink ArXiv

Research #Graphene 🔬 ResearchAnalyzed: Jan 10, 2026 07:12

Synergistic Terahertz Response in Graphene: A Novel Approach to Energy Harvesting

Published:Dec 26, 2025 15:34

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1 min read

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ArXiv

Analysis

The research, published on ArXiv, explores the potential of combining coherent absorption and plasmon-enhanced graphene for improved terahertz photo-thermoelectric response. This could lead to advancements in energy harvesting and high-frequency detection applications.

Key Takeaways

•Explores the use of graphene for terahertz detection and energy harvesting.
•Investigates the synergy between coherent absorption and plasmon enhancement.
•Published on ArXiv, suggesting early-stage research and potential for future development.

Reference

“The research focuses on the synergistic effect of coherent absorption and plasmon-enhanced graphene.”

Permalink ArXiv

Research #Knowledge Graph 🔬 ResearchAnalyzed: Jan 10, 2026 07:13

Beyond Entity Variance: Deep Dive into Uncertainty in Knowledge Graph Embeddings

Published:Dec 26, 2025 12:38

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1 min read

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ArXiv

Analysis

This ArXiv paper addresses a crucial aspect of knowledge graph embeddings by moving beyond simple variance measures of entities. The research likely offers valuable insights into more robust and nuanced uncertainty modeling for knowledge graph representation and inference.

Key Takeaways

•Explores uncertainty modeling in the context of knowledge graph embeddings.
•Suggests limitations of using only entity variance as a measure of uncertainty.
•Likely proposes new methods for representing and reasoning with uncertain knowledge.

Reference

“The research focuses on decomposing uncertainty in probabilistic knowledge graph embeddings.”

Permalink ArXiv

Research #BFS 🔬 ResearchAnalyzed: Jan 10, 2026 07:14

BLEST: Accelerating Breadth-First Search with Tensor Cores

Published:Dec 26, 2025 10:30

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1 min read

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ArXiv

Analysis

This research paper introduces BLEST, a novel approach to significantly speed up Breadth-First Search (BFS) algorithms using tensor cores. The authors likely demonstrate impressive performance gains compared to existing methods, potentially impacting various graph-based applications.

Key Takeaways

•BLEST is a new method for accelerating BFS algorithms.
•The method utilizes tensor cores for improved performance.
•The research likely presents benchmark results showing the efficiency gains.

Reference

“BLEST leverages tensor cores for efficient BFS.”

Permalink ArXiv

Research #Graph Theory 🔬 ResearchAnalyzed: Jan 10, 2026 07:15

Novel Characterization of Graphs Quasi-Isometric to Bounded Treewidth Graphs

Published:Dec 26, 2025 09:45

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1 min read

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ArXiv

Analysis

This research explores a novel characterization, which is significant for graph theory. The study's focus on quasi-isometries provides valuable insights into the geometric properties of graphs.

Key Takeaways

•Focuses on a specific graph property – quasi-isometry.
•Investigates the relationship with bounded treewidth graphs.
•Potentially provides new algorithmic approaches or structural insights.

Reference

“The paper investigates graphs quasi-isometric to graphs of bounded treewidth.”

Permalink ArXiv

Research #Synchronization 🔬 ResearchAnalyzed: Jan 10, 2026 07:16

Novel Synchronization Landscape Analysis using Graph Skeletons

Published:Dec 26, 2025 09:20

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1 min read

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ArXiv

Analysis

This research explores the synchronization landscape induced by graph skeletons, a niche but important area within graph theory and AI. The paper's focus on benign nonconvexity suggests potential improvements in optimization algorithms used in synchronization tasks.

Key Takeaways

•Investigates the synchronization landscape.
•Utilizes graph skeletons for analysis.
•Focuses on the concept of benign nonconvexity.

Reference

“Benign Nonconvexity of Synchronization Landscape Induced by Graph Skeletons.”

Permalink ArXiv

Research #Action Recognition 🔬 ResearchAnalyzed: Jan 10, 2026 07:17

Human-Centric Graph Representation for Multimodal Action Recognition

Published:Dec 26, 2025 08:17

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1 min read

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ArXiv

Analysis

This research explores a novel approach to multimodal action recognition, leveraging graph representation learning with a human-centric perspective. The approach, termed "Patch as Node", is promising and suggests a shift towards more interpretable and robust action understanding.

Key Takeaways

•Focuses on a human-centric approach to action recognition.
•Utilizes graph representation learning techniques.
•Proposes the "Patch as Node" methodology for multimodal data integration.

Reference

“The article is sourced from ArXiv.”

Permalink ArXiv

Research #Graph Theory 🔬 ResearchAnalyzed: Jan 10, 2026 07:19

Shellability of 3-Cut Complexes in Hexagonal Grid Graphs: A Research Analysis

Published:Dec 25, 2025 18:11

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1 min read

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ArXiv

Analysis

The article's subject matter is highly specialized, focusing on a specific area of graph theory. The potential impact is limited to researchers working in this field, with negligible broader implications.

Key Takeaways

•The research focuses on the properties of complexes within hexagonal grid graphs.
•Shellability is a key concept analyzed in the paper.
•The target audience is primarily academic researchers in graph theory.

Reference

“The paper examines the shellability of 3-cut complexes within hexagonal grid graphs.”

Permalink ArXiv

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