Python implementation of Lightning-rod Agent, the Stack4Things board-side probe

Overview
This is a library for training and applying sparse fine-tunings with torch and transformers.

This is a library for training and applying sparse fine-tunings with torch and transformers. Please refer to our paper Composable Sparse Fine-Tuning f

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Checkout some cool self-projects you can try your hands on to curb your boredom this December!

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Stacs-ci - A set of modules to enable integration of STACS with commonly used CI / CD systems

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Official implementation of Neural Bellman-Ford Networks (NeurIPS 2021)

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CS50's Introduction to Artificial Intelligence Test Scripts

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This repository is the official implementation of Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regularized Fine-Tuning (NeurIPS21).

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PyTorch implementation of "Learn to Dance with AIST++: Music Conditioned 3D Dance Generation."

Learn to Dance with AIST++: Music Conditioned 3D Dance Generation. Installation pip install -r requirements.txt Prepare Dataset bash data/scripts/pre

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Deep learning model, heat map, data prepo

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UMEC: Unified Model and Embedding Compression for Efficient Recommendation Systems

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Trading Gym is an open source project for the development of reinforcement learning algorithms in the context of trading.

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Anomaly detection in multi-agent trajectories: Code for training, evaluation and the OpenAI highway simulation.

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ICCV2021 Paper: AutoShape: Real-Time Shape-Aware Monocular 3D Object Detection

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DeepLM: Large-scale Nonlinear Least Squares on Deep Learning Frameworks using Stochastic Domain Decomposition (CVPR 2021)

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Experiments with the Robust Binary Interval Search (RBIS) algorithm, a Query-Based prediction algorithm for the Online Search problem.

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An executor that performs image segmentation on fashion items

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Code for the paper "Offline Reinforcement Learning as One Big Sequence Modeling Problem"

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A python library for self-supervised learning on images.

Lightly is a computer vision framework for self-supervised learning. We, at Lightly, are passionate engineers who want to make deep learning more effi

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