Pinned Repositories
Sequoia
The Research Tree - A playground for research at the intersection of Continual, Reinforcement, and Self-Supervised Learning.
mttl
Building modular LMs with parameter-efficient fine-tuning.
Continuous_Control_DDPG
Udacity Reinforcement Learning nanodegree Project 2
flash_attention_educational
Implementation of flash attention for educational purposes.
latent_CL
Codebase used in the paper "Foundational Models for Continual Learning: An Empirical Study of Latent Replay".
LMC
Codebase for the paper titled "Continual learning with local module selection"
machine-learning-dgm
Learning to Remember what to Remember: A Synaptic Plasticity Driven Framework for Continual Learning
Stochastic_VI_LDA
Stochastic Variational Inference for Latent Dirichlet Allocation
osaka
Codebase for "Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning". This is a ServiceNow Research project that was started at Element AI.
SCoLe-SCaling-Continual-Learning
Official Code for "Challenging Common Assumptions about Catastrophic Forgetting and Knowledge Accumulation", CoLLas 2023.
oleksost's Repositories
oleksost/latent_CL
Codebase used in the paper "Foundational Models for Continual Learning: An Empirical Study of Latent Replay".
oleksost/LMC
Codebase for the paper titled "Continual learning with local module selection"
oleksost/flash_attention_educational
Implementation of flash attention for educational purposes.
oleksost/CausalMBRL
Official data and code for our paper Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning
oleksost/CLIP
Contrastive Language-Image Pretraining
oleksost/continuum
A clean and simple data loading library for Continual Learning
oleksost/convergence_plots
oleksost/CTrLBenchmark
Benchmark for Lifelong learning research
oleksost/cuda_mode_lectures
Material for cuda-mode lectures
oleksost/examples
A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
oleksost/get-started-with-JAX
The purpose of this repo is to make it easy to get started with JAX, Flax, and Haiku. It contains my "Machine Learning with JAX" series of tutorials (YouTube videos and Jupyter Notebooks) as well as the content I found useful while learning about the JAX ecosystem.
oleksost/google-research
Google Research
oleksost/GPU-Puzzles
Solve puzzles. Learn CUDA.
oleksost/hopfield-layers
Hopfield Networks is All You Need
oleksost/lamini
oleksost/lm-evaluation-harness
A framework for few-shot evaluation of autoregressive language models.
oleksost/machine-learning-interview
Machine Learning Interviews from FAANG, Snapchat, LinkedIn. I have offers from Snapchat, Coupang, Stitchfix etc. Blog: mlengineer.io.
oleksost/minGPT
A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training
oleksost/mol_tool_hw
oleksost/multi_gpu_training
oleksost/multihead_uncertainty
oleksost/neural_production_systems
oleksost/nngeometry
NNGeometry is a PyTorch library for computing Fisher Information Matrices and Neural Tangent Kernels
oleksost/open-instruct
oleksost/patching
Patching open-vocabulary models by interpolating weights
oleksost/RoutingNetworks
oleksost/slot-attention
Implementation of Slot Attention from GoogleAI
oleksost/slot-attention-pytorch
Pytorch Implementation of paper "Object-Centric Learning with Slot Attention"
oleksost/stk
oleksost/Triton-Puzzles
Puzzles for learning Triton