226 skills found · Page 3 of 8
jjiantong / FastPGMFast Parallel Probabilistic Graphical Model Learning and Inference [IPDPS'22, PPoPP'23, USENIX ATC'24]
lorenzoh / DataLoaders.jlA parallel iterator for large machine learning datasets that don't fit into memory inspired by PyTorch's `DataLoader` class.
Improbable-AI / PqlParallel Q-Learning: Scaling Off-policy Reinforcement Learning under Massively Parallel Simulation
XiaoSongXS / HPC NotesPersonal Notes for Learning HPC & Parallel Computation [NO LONGER ADDING NEW CONTENT]
wangkuiyi / LassoLASSO is a parallel regression model learning system
Paranioar / UniPT[CVPR2024] The code of "UniPT: Universal Parallel Tuning for Transfer Learning with Efficient Parameter and Memory"
h3lio5 / Linguistic Style Transfer PytorchImplementation of "Disentangled Representation Learning for Non-Parallel Text Style Transfer(ACL 2019)" in Pytorch
Tinglok / CVCCVC: Contrastive Learning for Non-parallel Voice Conversion (INTERSPEECH 2021, in PyTorch)
heathermiller / MenthorParallelizing Machine Learning-- Functionally.
lancopku / SMAEThis is the code for "Learning Sentiment Memories for Sentiment Modification without Parallel Data".
zhjy2016 / SPLUTOfficial code for ECCV2022 paper: Learning Series-Parallel Lookup Tables for Efficient Image Super-Resolution
chenhu96 / Self Supervised MRI ReconstructionSelf-Supervised Learning for MRI Reconstruction with a Parallel Network Training Framework. (MICCAI 2021, official code)
deep-reinforcement-learning-book / Chapter16 Robot Learning In SimulationChapter 16 Robot Learning in Simulation in book Deep Reinforcement Learning: example of Sawyer robot learning to reach the target with paralleled Soft Actor-Critic (SAC) algorithm, using PyRep for Sawyer robot simulation and game building. The environment is wrapped into OpenAI Gym format.
dalgu90 / Splitnet WrnCode for ICML 2017 paper, SplitNet: Learning to Semantically Split Deep Networks for Parameter Reduction and Model Parallelization
CoffeeBeforeArch / Parallel ProgrammingA collection of code examples for learning parallel programming concepts
uoguelph-mlrg / Theano MPIMPI Parallel framework for training deep learning models built in Theano
hypergol / HypergolHypergol is a Data Science/Machine Learning productivity toolkit to accelerate any projects into production with autogenerated code, standardised structure for data and ML and parallel processing out-of-the-box.
suryakiranmg / Dynamic Movement Primitives And Imitation Learning RoboticsDynamic movement primitives (DMPs) are a method of trajectory control/planning from Stefan Schaal’s lab. Complex movements have long been thought to be composed of sets of primitive action ‘building blocks’ executed in sequence and \ or in parallel, and DMPs are a proposed mathematical formalization of these primitives. The difference between DMPs and previously proposed building blocks is that each DMP is a nonlinear dynamical system. The basic idea is that you take a dynamical system with well specified, stable behavior and add another term that makes it follow some interesting trajectory as it goes about its business. The DMP differential equations (Transformation System, Canonical System, Non-linear Function) realize a general way of generating point-to-point movements. Imitation learning using linear regression is performed to compute the weight factor W from a demonstrated trajectory dataset, given by a teacher. The quality of the imitation is evaluated by comparing the training data with the data generated by the DMP.
jakezhaojb / Deep Music AutoencoderThe repo involves a Deep Learning method, Stacked Denoising Autoencoder. The repo exploits "paracel", which is a new parallel computing framework
ContinuumIO / ElmPhase I & part of Phase II of NASA SBIR - Parallel Machine Learning on Satellite Data
