## Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains NeurIPS 2020 (spotlight) - Matthew Tancik* UC Berkeley Pratul Srinivasan* UC Berkeley Ben Mildenhall* UC Berkeley Sara Fridovich-Keil UC Berkeley Nithin Raghavan UC Berkeley Utkarsh Singhal UC Berkeley Ravi Ramamoorthi UC San Diego Jonathan T. Barron Google Research Ren Ng UC Berkeley *denotes equal contribution #### Paper #### Code ### Abstract We show that passing input points through a simple Four
Let’s take a step back and examine a machine learning architecture that has become the go-to for image recognition and computer vision.
論文 コメントする 小規模データセットに対するニューラルネットの汎化性能の理由に迫る論文：Modern Neural Networks Generalize on Small Data Sets NeurIPS 2018の論文で「Modern Neural Networks Generalize on Small Data Sets」という論文があったので読んでみた。 ニューラルネット
Modern artificial neural networks, including convolutional neural networks and vision transformers, have mastered several computer vision tasks, including object recognition. However, there are many significant differences between the behavior and robustness of these systems and of the human visual system. Deep neural networks remain brittle and susceptible to many changes in the image that do not cause humans to misclassify images. Part of this different behavior may be explained by the type of features hu
Neural Network and Genetic Algorithm Software for solving prediction, classification, forecasting, and optimization problems
Complexity science for understanding AI: from the dynamics of complex networks to collective effects of interacting neural networks
Abstract page for arXiv paper 2211.08486v4: Scalar Invariant Networks with Zero Bias
# StampCA: Growing Emoji with Conditional Neural Cellular Automata When a baby is born, it doesn’t just appear out of nowhere -- it starts as a single cell. This seed cell contains all the information needed to replicate and grow into a full adult. In biology, we call this process morphogenesis: the development of a seed into a structured design. Morphogenesis builds up an embyro. https://www.nature.com/articles/s41467-018-04155-2 Of course, if there’s a cool biological phenomenon, someone has tried to
New imaging techniques map the self-organizing patterns of neuronal networks, showing how brain cells form clusters to build functional circuits in the lab
Les réseaux de neurones et la ressemblance des possibles / Neural Networks and the Resemblance of Possibles 02/2017 Imagination artificielle Par-delà l’effet de mode provoqué par la mise à disposition du code source de plusieurs réseaux de neurones et la médiatisation orchestrée par certains acteurs du marché, j’aimerais formuler l’hypothèse de certaines implications conceptuelles de ces réseaux récursifs de neurones (RNN). Pour formuler celle-ci, je soutiendrais que les RNN intensifient