ermongroup / fast_feedforward_computation

Related projects ⓘ

Alternatives and complementary repositories for fast_feedforward_computation

• yilundu / ebm_compositionality
  [NeurIPS'20] Code for the Paper Compositional Visual Generation and Inference with Energy Based Models
  ☆43Updated last year
• Newbeeer / Anytime-Auto-Regressive-Model
  Code for ICLR 2021 Paper, "Anytime Sampling for Autoregressive Models via Ordered Autoencoding"
  ☆24Updated last year
• NingMiao / InstaAug
  ☆13Updated last year
• cunningham-lab / igr
  ☆31Updated 4 years ago
• shwinshaker / LipGrow
  An adaptive training algorithm for residual network
  ☆14Updated 4 years ago
• RobertCsordas / linear_layer_as_attention
  The official repository for our paper "The Dual Form of Neural Networks Revisited: Connecting Test Time Predictions to Training Patterns …
  ☆16Updated 11 months ago
• bergen / EdgeTransformer
  ☆21Updated 2 years ago
• srush / mamba-scans
  Blog post
  ☆16Updated 8 months ago
• ssnl / poisson_quasimetric_embedding
  Open source code for paper "On the Learning and Learnability of Quasimetrics".
  ☆32Updated last year
• facebookresearch / w2ot
  Euclidean Wasserstein-2 optimal transportation
  ☆43Updated last year
• hichamjanati / debiased-ot-barycenters
  ☆23Updated 3 years ago
• ruiqigao / recovery_likelihood
  ☆49Updated 3 years ago
• locuslab / monotone_op_net
  Monotone operator equilibrium networks
  ☆51Updated 4 years ago
• michaelsdr / sinkformers
  Transformers with doubly stochastic attention
  ☆40Updated 2 years ago
• facebookresearch / neural-scs
  Neural Fixed-Point Acceleration for Convex Optimization
  ☆29Updated 2 years ago
• minyoungg / overparam
  ☆40Updated last year
• justkolesov / Wasserstein1Benchmark
  A set of tests for evaluating large-scale algorithms for Wasserstein-1 transport computation (NeurIPS'22).
  ☆20Updated 2 months ago
• radarFudan / Curse-of-memory
  Curse-of-memory phenomenon of RNNs in sequence modelling
  ☆19Updated this week
• zhangjiong724 / spectral-RNN
  STABILIZING GRADIENTS FOR DEEP NEURAL NETWORKS VIA EFFICIENT SVD PARAMETERIZATION
  ☆16Updated 6 years ago
• apple / ml-agm
  ☆42Updated 6 months ago
• thu-ml / implicit-normalizing-flows
  Code for "Implicit Normalizing Flows" (ICLR 2021 spotlight)
  ☆34Updated 3 years ago
• tml-epfl / why-weight-decay
  Why Do We Need Weight Decay in Modern Deep Learning? [NeurIPS 2024]
  ☆49Updated last month
• yilundu / improved_contrastive_divergence
  [ICML'21] Improved Contrastive Divergence Training of Energy Based Models
  ☆62Updated 2 years ago
• IndustAI / learning-group-structure
  Code associated with our paper "Learning Group Structure and Disentangled Representations of Dynamical Environments"
  ☆15Updated last year
• facebookresearch / semi-discrete-flow
  code for "Semi-Discrete Normalizing Flows through Differentiable Tessellation"
  ☆24Updated last year
• thjashin / rodeo
  Gradient Estimation with Discrete Stein Operators (NeurIPS 2022)
  ☆17Updated 11 months ago
• bpucla / latent-space-EBM-prior
  ☆33Updated 4 years ago
• taufikxu / FD-ScoreMatching
  The official code for Efficient Learning of Generative Models via Finite-Difference Score Matching
  ☆12Updated last year
• NVlabs / VAEBM
  The Official PyTorch Implementation of "VAEBM: A Symbiosis between Variational Autoencoders and Energy-based Models" (ICLR 2021 spotlight…
  ☆54Updated 2 years ago
• yaohungt / Pointwise_Dependency_Neural_Estimation
  ☆19Updated 4 years ago