ppope / dimensions

Related projects: ⓘ

• MichaelArbel / GeneralizedEBM
  ☆52Updated last month
• cemanil / LNets
  Lipschitz Neural Networks described in "Sorting Out Lipschitz Function Approximation" (ICML 2019).
  ☆54Updated 4 years ago
• facebookresearch / BalancingGroups
  Simple data balancing baselines for worst-group-accuracy benchmarks.
  ☆39Updated 10 months ago
• ansuini / IntrinsicDimDeep
  Code for the intrinsic dimensionality estimate of data representations
  ☆75Updated 4 years ago
• iamalexkorotin / Wasserstein2GenerativeNetworks
  PyTorch implementation of "Wasserstein-2 Generative Networks" (ICLR 2021)
  ☆49Updated last year
• YannDubs / Invariant-Self-Supervised-Learning
  Pytorch code for "Improving Self-Supervised Learning by Characterizing Idealized Representations"
  ☆40Updated last year
• wgrathwohl / VERA
  ☆62Updated 7 months ago
• point0bar1 / ebm-anatomy
  PyTorch implementation of Algorithm 1 of "On the Anatomy of MCMC-Based Maximum Likelihood Learning of Energy-Based Models"
  ☆36Updated last month
• ruiqigao / recovery_likelihood
  ☆49Updated 3 years ago
• lorraine2 / implicit-hyper-opt
  ☆35Updated this week
• avirmaux / lipEstimation
  ☆56Updated last year
• locuslab / orthogonal-convolutions
  Implementations of orthogonal and semi-orthogonal convolutions in the Fourier domain with applications to adversarial robustness
  ☆41Updated 3 years ago
• MadryLab / BREEDS-Benchmarks
  ☆55Updated 4 years ago
• cunningham-lab / igr
  ☆31Updated 3 years ago
• bethgelab / InDomainGeneralizationBenchmark
  ☆33Updated 3 years ago
• bobby-he / bayesian-ntk
  Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'
  ☆26Updated 3 years ago
• gibipara92 / learning-explanations-hard-to-vary
  Code to implement the AND-mask and geometric mean to do gradient based optimization, from the paper "Learning explanations that are hard …
  ☆39Updated 3 years ago
• PolinaKirichenko / deep_feature_reweighting
  ☆102Updated 11 months ago
• zengyi-li / NMCE-release
  Code for Neural Manifold Clustering and Embedding
  ☆56Updated 2 years ago
• yilundu / improved_contrastive_divergence
  [ICML'21] Improved Contrastive Divergence Training of Energy Based Models
  ☆60Updated 2 years ago
• ermongroup / alignflow
  ☆32Updated 4 years ago
• yaodongyu / Rethink-BiasVariance-Tradeoff
  Rethinking Bias-Variance Trade-off for Generalization of Neural Networks
  ☆49Updated 3 years ago
• wgrathwohl / LSD
  Official Release of "Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling"
  ☆45Updated 4 years ago
• tml-epfl / sharpness-vs-generalization
  A modern look at the relationship between sharpness and generalization [ICML 2023]
  ☆42Updated last year
• js-d / sim_metric
  ☆32Updated 11 months ago
• michaelsdr / sinkformers
  Transformers with doubly stochastic attention
  ☆40Updated 2 years ago
• AnonymousNIPS2019 / DeepnetHessian
  The Full Spectrum of Deepnet Hessians at Scale: Dynamics with SGD Training and Sample Size
  ☆17Updated 5 years ago
• izmailovpavel / bnn_covariate_shift
  Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"
  ☆33Updated last year
• aniruddhraghu / meta-pretraining
  Code accompanying paper: Meta-Learning to Improve Pre-Training
  ☆36Updated 2 years ago
• AllanYangZhou / metalearning-symmetries
  Experiments for Meta-Learning Symmetries by Reparameterization
  ☆55Updated 3 years ago