lightonai / double-descent-curve

Related projects ⓘ

Alternatives and complementary repositories for double-descent-curve

• lightonai / newma-md
  Conformational exploration SARS-CoV-2 (coronavirus responsible for COVID-19)
  ☆16Updated 2 years ago
• lightonai / double-trouble-in-double-descent
  Double Trouble in the Double Descent Curve with Optical Processing Units.
  ☆12Updated 2 years ago
• lightonai / supervised-random-projections
  Python implementation of supervised PCA, supervised random projections, and their kernel counterparts.
  ☆20Updated 4 years ago
• lightonai / transfer-learning-opu
  Optical Transfer Learning
  ☆27Updated last year
• hashemghanem / OPU_Graph_Classifier
  Fast graph classifier with optical random features
  ☆12Updated 3 years ago
• lightonai / opu-benchmarks
  ML benchmarks performance featuring LightOn's Optical Processing Unit (OPU) vs CPU and GPU.
  ☆21Updated last year
• lightonai / reinforcement-learning-opu
  Code to perform Model-Free Episodic Control using Aurora OPUs
  ☆17Updated 4 years ago
• lightonai / principled-dfa-training
  Code for our paper on best practices to train neural networks with direct feedback alignment (DFA).
  ☆22Updated 5 years ago
• lightonai / lightonmuse
  Python client for the LightOn Muse API
  ☆14Updated 2 years ago
• lightonai / lightonml
  Python library for running large-scale computations on LightOn's OPUs
  ☆35Updated 2 years ago
• lightonai / newma
  Implementation of NEWMA: a new method for scalable model-free online change-point detection
  ☆46Updated 4 years ago
• lightonai / contrastive-embeddings-for-neural-architectures
  Architecture embeddings independent from the parametrization of the search space
  ☆15Updated 3 years ago
• lightonai / dfa-scales-to-modern-deep-learning
  Study on the applicability of Direct Feedback Alignment to neural view synthesis, recommender systems, geometric learning, and natural la…
  ☆84Updated 2 years ago
• jayanthkoushik / torch-gel
  Group elastic net implementation in PyTorch.
  ☆44Updated 4 years ago
• pfnet-research / einconv
  ☆46Updated 5 years ago
• f-dangel / hbp
  Hessian backpropagation (HBP): PyTorch extension of backpropagation for block-diagonal curvature matrix approximations
  ☆20Updated last year
• modestyachts / neural_kernels_code
  ☆36Updated 3 years ago
• rballester / ttrecipes
  Metamodeling, sensitivity analysis and visualization using the tensor train format
  ☆23Updated 2 years ago
• AlexanderMath / fasth
  Code for the article "What if Neural Networks had SVDs?", to be presented as a spotlight paper at NeurIPS 2020.
  ☆69Updated 3 months ago
• lightonai / lairgpt
  Inference code in Pytorch for GPT-like models, such as PAGnol, a family of models with up to 1.5B parameters, trained on datasets in Fren…
  ☆20Updated 2 years ago
• team-approx-bayes / BayesBiNN
  Code for the paper "Training Binary Neural Networks with Bayesian Learning Rule
  ☆37Updated 2 years ago
• maremun / quffka
  Quadrature-based features for kernel approximation
  ☆16Updated 6 years ago
• harryliew / SdLBFGS
  ☆24Updated 6 years ago
• tajanthan / pmf
  Proximal Mean-field for Neural Network Quantization
  ☆22Updated 4 years ago
• gd-zhang / Weight-Decay
  Regularization, Neural Network Training Dynamics
  ☆14Updated 4 years ago
• lightonai / akronomicon
  Public rankings of extreme-scale models
  ☆13Updated 3 years ago
• brain-research / mean-field-cnns
  ☆35Updated 5 years ago
• flaport / torch_eunn
  A Pytorch implementation of an efficient unitary neural network (https://arxiv.org/abs/1612.05231)
  ☆33Updated 4 years ago
• ChFrenkel / DirectRandomTargetProjection
  PyTorch-based code for training fully-connected and convolutional networks using backpropagation (BP), feedback alignment (FA), direct fe…
  ☆63Updated 3 years ago