xaviergonzalez
PhD student in statistics at Stanford in the @lindermanlab
@lindermanlabStanford University
xaviergonzalez's Stars
NX-AI/xlstm
Official repository of the xLSTM.
lucidrains/minGRU-pytorch
Implementation of the proposed minGRU in Pytorch
lindermanlab/S5
machine-discovery/deer
Parallelizing non-linear sequential models over the sequence length
NicolasZucchet/minimal-LRU
Non official implementation of the Linear Recurrent Unit (LRU, Orvieto et al. 2023)
jopetty/sfirah
HazyResearch/safari
Convolutions for Sequence Modeling
HazyResearch/zoology
Understand and test language model architectures on synthetic tasks.
jay1999ke/autodiff
Reverse Mode Automatic Differentiation (CPU + GPU)
karpathy/llm.c
LLM training in simple, raw C/CUDA
proger/accelerated-scan
Accelerated First Order Parallel Associative Scan
lindermanlab/elk
Scalable and Stable Parallelization of Nonlinear RNNS
google-research/computation-thru-dynamics
Understanding computation in artificial and biological recurrent networks through the lens of dynamical systems.
AndyShih12/paradigms
PyTorch implementation for "Parallel Sampling of Diffusion Models", NeurIPS 2023 Spotlight
kjytay/stanford-stats
My notes from class
state-spaces/mamba
Mamba SSM architecture
mathiasbynens/dotfiles
:wrench: .files, including ~/.macos — sensible hacker defaults for macOS
patrick-kidger/equinox
Elegant easy-to-use neural networks + scientific computing in JAX. https://docs.kidger.site/equinox/
nerdnik/PyCliqueTop_2023
Python version of MATLAB CliqueTop package by Chad Giusti PNAS 2015. Computes Betti curves from similarity matrices.
mattjj/pyhsmm
slinderman/recurrent-slds
Recurrent Switching Linear Dynamical Systems
lindermanlab/fos
Semi-NMF for Fos data
lindermanlab/dirichlet-tucker
Tucker decompositions with normalization constraints
shchur/ifl-tpp
Implementation of "Intensity-Free Learning of Temporal Point Processes" (Spotlight @ ICLR 2020)
i404788/s5-pytorch
Pytorch implementation of Simplified Structured State-Spaces for Sequence Modeling (S5)
jakechang98/stats320_bayesianICA
jeffheaton/t81_558_deep_learning
T81-558: Keras - Applications of Deep Neural Networks @Washington University in St. Louis
alexblnn/Notip
sjdavenport/pyrft
cvxpy/cvxpy
A Python-embedded modeling language for convex optimization problems.