Pinned Repositories
motif
Intrinsic Motivation from Artificial Intelligence Feedback
MAGE
Learning Action-Value Gradients in Model-based Policy Optimization
cheatsheet-translation
Translation of VIP cheatsheets https://stanford.edu/~shervine/teaching/cs-229.html
high_replay_ratio_continuous_control
Efficient seed-parallel implementation of "Breaking the Replay Ratio Barrier"
pytorch-conv2_1d
Pytorch implementation of (2+1)D spatiotemporal convolutions
pytorch-GAN-timeseries
GANs for time series generation in pytorch
pytorch-neural-enhance
Experiments on CNN-based image enhancement in pytorch
randomist
Code for Policy Optimization as Online Learning with Mediator Feedback
rl-algs-cheatsheet
RL poster-shaped cheatsheet
tgan-pytorch
A PyTorch implementation of Temporal Generative Adversarial Nets with Singular Value Clipping
proceduralia's Repositories
proceduralia/pytorch-GAN-timeseries
GANs for time series generation in pytorch
proceduralia/pytorch-neural-enhance
Experiments on CNN-based image enhancement in pytorch
proceduralia/high_replay_ratio_continuous_control
Efficient seed-parallel implementation of "Breaking the Replay Ratio Barrier"
proceduralia/pytorch-conv2_1d
Pytorch implementation of (2+1)D spatiotemporal convolutions
proceduralia/tgan-pytorch
A PyTorch implementation of Temporal Generative Adversarial Nets with Singular Value Clipping
proceduralia/rl-algs-cheatsheet
RL poster-shaped cheatsheet
proceduralia/randomist
Code for Policy Optimization as Online Learning with Mediator Feedback
proceduralia/cheatsheet-translation
Translation of VIP cheatsheets https://stanford.edu/~shervine/teaching/cs-229.html
proceduralia/brax
Massively parallel rigidbody physics simulation on accelerator hardware.
proceduralia/bsuite
bsuite is a collection of carefully-designed experiments that investigate core capabilities of a reinforcement learning (RL) agent
proceduralia/experiment_buddy
proceduralia/proceduralia.github.io
proceduralia/TCN
Sequence modeling benchmarks and temporal convolutional networks
proceduralia/vllm
A high-throughput and memory-efficient inference and serving engine for LLMs