This is the official project page including the paper, code, simulation, baseline models and the dataset.
CODE WILL BE RELEASED SOON.
Anomaly Detection in Multi-Agent Trajectories for Automated Driving
Julian Wiederer, Arij Bouazizi, Marco Troina, Ulrich Kressel, Vasileios Belagiannis
Accepted for poster at CoRL_2021 in London, UK.
Graph Contrastive Learning with Augmentations PyTorch implementation for Graph Contrastive Learning with Augmentations [poster] [appendix] Yuning You*
PyTorch Image Models Sponsors What's New Introduction Models Features Results Getting Started (Documentation) Train, Validation, Inference Scripts Awe
TriageSQL The dataset and source code for our paper: "Did You Ask a Good Question? A Cross-Domain Question Intention Classification Benchmark for Text
The first comprehensive Robustness investigation benchmark on large-scale dataset ImageNet regarding ARchitecture design and Training techniques towards diverse noises.
iWildCam and FMoW baselines (WILDS) This repository was originally forked from the official repository of WILDS datasets (commit 7e103ed) For general
Deep Networks from the Principle of Rate Reduction This repository is the official PyTorch implementation of the paper Deep Networks from the Principl
Caffe Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by the Berkeley Vision and Learning Cent
STAC Catalog Discovery Simple STAC discovery tool. Just paste the STAC Catalog link and press Enter. Details STAC Discovery tool enables discovering d
vision_transformers This is my personnal repo to implement new transofrmers based and other computer vision DL models I am currenlty working without a
Cockpit: A Practical Debugging Tool for Training Deep Neural Networks
Overview This is a set of simple scripts to process the Imagenet-1K dataset as TFRecords and make index files for NVIDIA DALI. Make TFRecords To run t
NanoDet-Plusā”Super fast and lightweight anchor-free object detection model. š„Only 980 KB(int8) / 1.8MB (fp16) and run 97FPS on cellphoneš„
Denoising Normalizing Flow Christian Horvat and Jean-Pascal Pfister 2021 We combine Normalizing Flows (NFs) and Denoising Auto Encoder (DAE) by introd
This tool uses Deep Learning to help you draw and write with your hand and webcam. A Deep Learning model is used to try to predict whether you want to have 'pencil up' or 'pencil down'.
PySwarms is an extensible research toolkit for particle swarm optimization (PSO) in Python. It is intended for swarm intelligence researchers, practit
StockPredictions Use classic tricks, neural networks, deep learning, genetic programming and other methods to predict stock and market movements. Both
JWST Calibration Pipeline JWST requires Python 3.7 or above and a C compiler for dependencies. Linux and MacOS platforms are tested and supported. Win
This is the official PyTorch implementation of the ALBEF paper [Blog]. This repository supports pre-training on custom datasets, as well as finetuning on VQA, SNLI-VE, NLVR2, Image-Text Retrieval on
Cats-and-dogs-classifier This is my first ML model which can classify between cats and dogs. Here the accuracy is around 75%, however , the accuracy c
Jump Reward Inference for 1D Music Rhythmic State Spaces An implementation of the probablistic jump reward inference model for music rhythmic informat
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