Implicit Deep Adaptive Design (iDAD) This code supports the NeurIPS paper 'Implicit Deep Adaptive Design: Policy-Based Experimental Design without Lik

Python inverse kinematics for your robot model based on Pinocchio.

This repository contains code to reproduce results for submission NeurIPS 2021, "Momentum Centering and Asynchronous Update for Adaptive Gradient Meth

LERP : Label-dependent and event-guided interpretable disease risk prediction using EHRs This is the code for the LERP. Dataset The dataset used is MI

ProbAI 2021 - Probabilistic Programming and Variational Inference Tutorial with Pryo Day 1 (June 14) Slides Notebook: students_PPLs_Intro Notebook: so

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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

Learning to Track with Object Permanence A video-based MOT approach capable of tracking through full occlusions: Learning to Track with Object Permane

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Gender-classification This is a ML model to classify Male and Females using some physical characterstics Data. Python Libraries like Pandas,Numpy and

Cooper About Cooper is a toolkit for Lagrangian-based constrained optimization in Pytorch. This library aims to encourage and facilitate the study of

A plug-and-play library for neural networks written in Python!

ONCE Benchmark This is a reproduced benchmark for 3D object detection on the ONCE (One Million Scenes) dataset. The code is mainly based on OpenPCDet.

RoRD Rotation-Robust Descriptors and Orthographic Views for Local Feature Matching Project Page | Paper link Evaluation and Datasets MMA : Training on

self-supervised-landmarks Repository for self-supervised landmark discovery Requirements pytorch pynrrd (for 3d images) Usage The use of this models i

Camera Distortion-aware 3D Human Pose Estimation in Video with Optimization-based Meta-Learning This is the official repository of "Camera Distortion-

Single-Cell Image Analysis Package Scimap is a scalable toolkit for analyzing spatial molecular data. The underlying framework is generalizable to spa

tch-rs Rust bindings for the C++ api of PyTorch. The goal of the tch crate is to provide some thin wrappers around the C++ PyTorch api (a.k.a. libtorc

SAAVN SAAVN Code release for paper "Sound Adversarial Audio-Visual Navigation,IC

Trainable multi-codebook quantization This repository implements a utility for use with PyTorch, and ideally GPUs, for training an efficient quantizer