MLSpace: Hassle-free machine learning & deep learning development

Last update: Jan 03, 2023

Overview

MLSpace

Hassle-Free Machine Learning & Deep Learning Development

No need to worry about CUDA
No need to worry about cuDNN
No need to worry about TensorFlow version
No need to worry about PyTorch version
No need to install any libraries

coming soon

NOTE: PRs are currently not accepted. All PRs will be closed. Please use issues instead.

Owner

abhishek thakur

Kaggle: www.kaggle.com/abhishek

GitHub Repository https://mlspace.readthedocs.io/en/latest/

Codes accompanying the paper "Learning Nearly Decomposable Value Functions with Communication Minimization" (ICLR 2020)

NDQ: Learning Nearly Decomposable Value Functions with Communication Minimization Note This codebase accompanies paper Learning Nearly Decomposable Va

69 Nov 26, 2022

A generalized framework for prototyping full-stack cooperative driving automation applications under CARLA+SUMO.

OpenCDA OpenCDA is a SIMULATION tool integrated with a prototype cooperative driving automation (CDA; see SAE J3216) pipeline as well as regular autom

726 Dec 29, 2022

CL-Gym: Full-Featured PyTorch Library for Continual Learning

CL-Gym: Full-Featured PyTorch Library for Continual Learning CL-Gym is a small yet very flexible library for continual learning research and developme

36 Dec 25, 2022

This Jupyter notebook shows one way to implement a simple first-order low-pass filter on sampled data in discrete time.

How to Implement a First-Order Low-Pass Filter in Discrete Time We often teach or learn about filters in continuous time, but then need to implement t

4 Aug 24, 2022

Code for the paper: On Pathologies in KL-Regularized Reinforcement Learning from Expert Demonstrations

Non-Parametric Prior Actor-Critic (N-PPAC) This repository contains the code for On Pathologies in KL-Regularized Reinforcement Learning from Expert D

5 May 13, 2022

SparseInst: Sparse Instance Activation for Real-Time Instance Segmentation, CVPR 2022

SparseInst 🚀 A simple framework for real-time instance segmentation, CVPR 2022 by Tianheng Cheng, Xinggang Wang†, Shaoyu Chen, Wenqiang Zhang, Qian Z

458 Jan 05, 2023

Augmented CLIP - Training simple models to predict CLIP image embeddings from text embeddings, and vice versa.

Train aug_clip against laion400m-embeddings found here: https://laion.ai/laion-400-open-dataset/ - note that this used the base ViT-B/32 CLIP model. S

55 Sep 13, 2022

This repo is the official implementation of "L2ight: Enabling On-Chip Learning for Optical Neural Networks via Efficient in-situ Subspace Optimization".

L2ight is a closed-loop ONN on-chip learning framework to enable scalable ONN mapping and efficient in-situ learning. L2ight adopts a three-stage learning flow that first calibrates the complicated p

9 Jul 14, 2022

Learning What and Where to Draw

###Learning What and Where to Draw Scott Reed, Zeynep Akata, Santosh Mohan, Samuel Tenka, Bernt Schiele, Honglak Lee This is the code for our NIPS 201

337 Nov 18, 2022

Implementation for the EMNLP 2021 paper "Interactive Machine Comprehension with Dynamic Knowledge Graphs".

Interactive Machine Comprehension with Dynamic Knowledge Graphs Implementation for the EMNLP 2021 paper. Dependencies apt-get -y update apt-get instal

19 Aug 23, 2022

This repo implements several applications of the proposed generalized Bures-Wasserstein (GBW) geometry on symmetric positive definite matrices.

GBW This repo implements several applications of the proposed generalized Bures-Wasserstein (GBW) geometry on symmetric positive definite matrices. Ap

0 Oct 22, 2021

MLSpace: Hassle-free machine learning & deep learning development

Related tags

Overview

MLSpace

Hassle-Free Machine Learning & Deep Learning Development

Owner

abhishek thakur

Codes accompanying the paper "Learning Nearly Decomposable Value Functions with Communication Minimization" (ICLR 2020)

A generalized framework for prototyping full-stack cooperative driving automation applications under CARLA+SUMO.

CL-Gym: Full-Featured PyTorch Library for Continual Learning

This Jupyter notebook shows one way to implement a simple first-order low-pass filter on sampled data in discrete time.

Code for the paper: On Pathologies in KL-Regularized Reinforcement Learning from Expert Demonstrations

SparseInst: Sparse Instance Activation for Real-Time Instance Segmentation, CVPR 2022

Augmented CLIP - Training simple models to predict CLIP image embeddings from text embeddings, and vice versa.

This repo is the official implementation of "L2ight: Enabling On-Chip Learning for Optical Neural Networks via Efficient in-situ Subspace Optimization".

Learning What and Where to Draw

Implementation for the EMNLP 2021 paper "Interactive Machine Comprehension with Dynamic Knowledge Graphs".

This repo implements several applications of the proposed generalized Bures-Wasserstein (GBW) geometry on symmetric positive definite matrices.

You Only 👀 One Sequence

Isaac Gym Reinforcement Learning Environments

DL & CV-based indicator toolset for the vehicle drivers via live dash-cam footage.

Dynamic Slimmable Network (CVPR 2021, Oral)

Repo for flood prediction using LSTMs and HAND

Revisiting Discriminator in GAN Compression: A Generator-discriminator Cooperative Compression Scheme (NeurIPS2021)

Contrastive Learning of Structured World Models

Pytorch library for seismic data augmentation

Survival analysis in Python