Alternatives and similar repositories for Markov

Users that are interested in Markov are comparing it to the libraries listed below

• machine-discovery / deer
  Parallelizing non-linear sequential models over the sequence length
  ☆56Updated 7 months ago
• aadityasingh / icl-dynamics
  ☆25Updated 9 months ago
• GFNOrg / GFlowNet-EM
  Code for GFlowNet-EM, a novel algorithm for fitting latent variable models with compositional latents and an intractable true posterior.
  ☆42Updated 2 years ago
• AndPotap / einsum-search
  ☆33Updated last year
• abietti / transformer-birth
  ☆19Updated 2 years ago
• aradha / deep_neural_feature_ansatz
  Code for verifying deep neural feature ansatz
  ☆21Updated 2 years ago
• Ping-C / optimizer
  This repository includes code to reproduce the tables in "Loss Landscapes are All You Need: Neural Network Generalization Can Be Explaine…
  ☆40Updated 2 years ago
• locuslab / edge-of-stability
  ☆73Updated last year
• Benjamin-Walker / selective-ssms-and-linear-cdes
  Code for "Theoretical Foundations of Deep Selective State-Space Models" (NeurIPS 2024)
  ☆15Updated last year
• kazuki-irie / kv-memory-brain
  Official Code Repository for the paper "Key-value memory in the brain"
  ☆31Updated 11 months ago
• AhmedImtiazPrio / grok-adversarial
  Deep Networks Grok All the Time and Here is Why
  ☆38Updated last year
• fangyuan-ksgk / selective-attention-transformer
  Unofficial Implementation of Selective Attention Transformer
  ☆20Updated last year
• KindXiaoming / Omnigrok
  Omnigrok: Grokking Beyond Algorithmic Data
  ☆62Updated 2 years ago
• joneswack / dp-rfs
  This repository contains PyTorch implementations of various random feature maps for dot product kernels.
  ☆22Updated last year
• thjashin / multires-conv
  Sequence Modeling with Multiresolution Convolutional Memory (ICML 2023)
  ☆127Updated 2 years ago
• bhoov / energy-transformer-jax
  The Energy Transformer block, in JAX
  ☆63Updated 2 years ago
• DeqingFu / transformers-icl-second-order
  Official repository for our paper, Transformers Learn Higher-Order Optimization Methods for In-Context Learning: A Study with Linear Mode…
  ☆19Updated last year
• allenbai01 / transformers-as-statisticians
  ☆34Updated 2 years ago
• sustcsonglin / flash-linear-rnn
  Implementations of various linear RNN layers using pytorch and triton
  ☆54Updated 2 years ago
• wesg52 / universal-neurons
  Universal Neurons in GPT2 Language Models
  ☆30Updated last year
• tml-epfl / why-weight-decay
  Why Do We Need Weight Decay in Modern Deep Learning? [NeurIPS 2024]
  ☆70Updated last year
• chengxiang / LinearTransformer
  Pytorch code for experiments on Linear Transformers
  ☆24Updated 2 years ago
• shikaiqiu / compute-better-spent
  ☆62Updated last year
• google-deepmind / spectral_ssm
  ☆35Updated last year
• expz / annotated-hyena
  An annotated implementation of the Hyena Hierarchy paper
  ☆34Updated 2 years ago
• formll / dog
  DoG is SGD's Best Friend: A Parameter-Free Dynamic Step Size Schedule
  ☆64Updated 2 years ago
• jopetty / word-problem
  Experiments on the impact of depth in transformers and SSMs.
  ☆40Updated 3 months ago
• taufeeque9 / codebook-features
  Sparse and discrete interpretability tool for neural networks
  ☆64Updated 2 years ago
• srush / mamba-primer
  ☆39Updated last year
• IdoAmos / not-from-scratch
  ☆33Updated last year