neural network

"We introduce TorchLean, a framework in the Lean 4 theorem prover that treats learned models as first-class mathematical objects with a single, precise semantics shared by execution and verification."

"Results show FR provides spectral calibration, yielding modest XTC improvements and reduced inter-listener IPI imbalance. DIR delivers the most consistent sound-zone separation gains (10.05 dB average IZI/IPI). RS-HRTF dominates binaural separation, boosting XTC by +2.38/+2.89 dB (average 4.51 to 7.91 dB), primarily above 2 kHz, while introducing mild listener-dependent IZI/IPI shifts."

"This platform is structured around a curriculum that allows you to learn step-by-step from basic mathematics to the core structure of deep learning."

"We quantify, uniformly over time and with high probability, the discrepancy between the predictions of a two-layer neural network trained by stochastic gradient descent (SGD) and their mean-field limit, for quadratic loss and ridge regularization."

"We introduce TorchLean, a framework in the Lean 4 theorem prover that treats learned models as first-class mathematical objects with a single, precise semantics shared by execution and verification."

"By adding more variations of existing images, the model can improve its ability to classify images effectively."

"We find that VLMs exhibit robust congruency effects across all tasks, with larger models systematically resolving conflicts more effectively than smaller models."

"We demonstrate through systematic experiments that frequency prefactors exhibit limited trainability: movement is constrained to approximately +/-1 units with typical learning rates."

"This article explains DeepLearning, which is one of the learning methods that exists within AI, where machine learning exists within the larger framework."

"Tessera is an activation-based protocol that tries to solve this."

"Transformerを一言で表すなら、「全ての入力を同時に見て、どこに注目すべきかを自ら学習するニューラルネットワークの設計図」"

"In this example, we will create a Keras Sequential model and train it on the Cars dataset."

""Unlike the Pong work that we did a few years ago, which represented years of painstaking scientific effort, this demonstration has been done in a matter of days by someone who previously had relatively little expertise working directly with biology," says Brett Kagan of Cortical Labs."

"I am trying to model a NN to receive input vector (~ 1000 components) and return a vector with 5 components."

"Both convolution and pooling have something in common. Both calculations are performed on a 'sliding window'."

"They fed genetic data from five mouse brains — 10.4 million individual cells with hundreds of genes per cell — into a custom machine learning algorithm. The program delivered maps that are a neuro-realtor’s dream, with known and novel subdivisions within larger brain regions."

"Experimental results demonstrate that applying weights generated by this method to cluster-based Voronoi Diagrams significantly enhances scalability, accuracy, and physical plausibility, while increasing precision compared to traditional methods."

"Experimental results demonstrate that MNAS-Unet outperforms NAS-Unet and other state-of-the-art models in segmentation accuracy on several medical image datasets..."

"This paper investigates the theoretical foundations of computing in superposition, establishing complexity bounds for explicit, provably correct algorithms."

"Dosidicus electronicus 🦑 A transparent cognitive sandbox disguised as a digital pet squid with a neural network you can see thinking"

"For example, in the field of phishing email detection, it comprehensively judges not only words and senders, but also the composition and habits of sentences, and similarities with past fraud cases to detect suspicious emails with high accuracy."

"When Enlightenment thinkers, like René Descartes or Gottfried Wilhelm Leibniz, first began using mathematics to effectively describe the physical world around us, they also suggested that the same kind of approach might be u"

"The goal is to detect ethanol molecules in the air passively, removing the friction of manual checks while maintaining a high safety standard."

"This paper introduces Stream Neural Networks (StNN), an execution paradigm designed for irreversible input streams."

"By representing cable-driven robots as graphs, with the rigid-bodies as nodes and the cables and contacts as edges, this model can quickly and accurately match the properties of other simulation models and real robots, while ingesting only partially observable inputs."

"This is a great dive into the linear algebra square matrix, its determinant, and the relationship with the correlation coefficient of statistics."