Siddhant Haldar

ViTaL. Accompanying codebase for paper"Touch begins where vision ends: Generalizable policies for contact-rich manipulation"

P3PO. Code for P3PO

robot-utility-models. Robot Utility Models are trained on a diverse set of environments and objects, and then can be deployed in novel environments with novel objects without any further data or training.

ok-robot. An open, modular framework for zero-shot, language conditioned pick-and-drop tasks in arbitrary homes.

dobb-e. Dobb·E: An open-source, general framework for learning household robotic manipulation

miniBET. Clean implementation of conditional and unconditional behavior transformer.

ffcv. FFCV: Fast Forward Computer Vision (and other ML workloads!)

dowhy. DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

lingam. Python package for causal discovery based on LiNGAM.

graphviz. Simple Python interface for Graphviz

cifar10_challenge. A challenge to explore adversarial robustness of neural networks on CIFAR10.

Open3D-ML. An extension of Open3D to address 3D Machine Learning tasks

skorch. A scikit-learn compatible neural network library that wraps PyTorch

minGPT. A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training

adversarial-attacks-pytorch. PyTorch implementation of adversarial attacks [torchattacks]

TCSVT-LightWeight-CNNs. Code for our IEEE TCSVT Paper: Lightweight Modules for Efficient Deep Learning based Image Restoration

adversarial-robustness-toolbox. Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams

pytorch-normalizing-flows. Normalizing flows in PyTorch. Current intended use is education not production.

gradient-checkpointing. Make huge neural nets fit in memory

chartify. Python library that makes it easy for data scientists to create charts.

awesome-domain-adaptation. A collection of AWESOME things about domain adaptation

Sequential-Data-Loader-and-Model-for-Variable-Length-Data. Data loader and model for variable length data in PyTorch

Disentanglement_NEURIPS_2019. On disentangling the menagerie of disentanglement papers

mnist_challenge. A challenge to explore adversarial robustness of neural networks on MNIST.

transformers. 🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.

BERT-related-papers. BERT-related papers

SCL. Implementation of "SCL: Towards Accurate Domain Adaptive Object Detection via Gradient Detach Based Stacked Complementary Losses"

SinGAN. Official pytorch implementation of the paper: "SinGAN: Learning a Generative Model from a Single Natural Image"

pytorch-cnn-visualizations. Pytorch implementation of convolutional neural network visualization techniques

TensorFlow-2.x-Tutorials. TensorFlow 2.x version's Tutorials and Examples, including CNN, RNN, GAN, Auto-Encoders, FasterRCNN, GPT, BERT examples, etc. TF 2.0版入门实例代码，实战教程。

RAdam. On the Variance of the Adaptive Learning Rate and Beyond

generative-inpainting-pytorch. A PyTorch reimplementation for paper Generative Image Inpainting with Contextual Attention (https://arxiv.org/abs/1801.07892)

GLCIC-PyTorch. A High-Quality PyTorch Implementation of "Globally and Locally Consistent Image Completion".

Deep-Tutorials-for-PyTorch. In-depth tutorials for implementing deep learning models on your own with PyTorch.

machine-learning-interview-questions. This repository is to prepare for Machine Learning interviews.

imgclsmob. Sandbox for training deep learning networks

deeplearning-models. A collection of various deep learning architectures, models, and tips

Image-Captioning-Attack. Codes for reproducing the adversarial attacks on image captioning systems in “Attacking Visual Language Grounding with Adversarial Examples: A Case Study on Neural Image Captioning,” ACL 2018 ​​​​​​​

mAP. mean Average Precision - This code evaluates the performance of your neural net for object recognition.

pytorch_classifiers. Almost any Image classification problem using pytorch

labelImg. LabelImg is now part of the Label Studio community. The popular image annotation tool created by Tzutalin is no longer actively being developed, but you can check out Label Studio, the open source data labeling tool for images, text, hypertext, audio, video and time-series data.

fastai. The fastai deep learning library

SSD-PyTorch. SSD (Single Shot MultiBox Detector) implement in PyTorch and OpenCV.

Deep-Reinforcement-Learning-Algorithms-with-PyTorch. PyTorch implementations of deep reinforcement learning algorithms and environments

recurrent-visual-attention. A PyTorch Implementation of "Recurrent Models of Visual Attention"

Awesome-Image-Inpainting. A curated list of image inpainting and video inpainting papers and resources

dataloaders. Pytorch and TensorFlow data loaders for several audio datasets

video-classification. Tutorial for video classification/ action recognition using 3D CNN/ CNN+RNN on UCF101

Fast-RCNN-Object-Detection-Pytorch. Python

flowpoints_ml. An intuitive approach to creating deep learning models

pytorch_geometric. Graph Neural Network Library for PyTorch

Attention-Augmented-Conv2d. Implementing Attention Augmented Convolutional Networks using Pytorch

PlaNet. Deep Planning Network: Control from pixels by latent planning with learned dynamics

PySnooper. Never use print for debugging again

CenterNet. Codes for our paper "CenterNet: Keypoint Triplets for Object Detection" .

Reinforcement-learning-in-computer-vision.

LaneNetRos. Ros node to use LaneNet to detect the lane in camera

CUDA-CNN-inference-with-thread-coarsening. Cuda

mpitutorial. MPI programming lessons in C and executable code examples

Operations_Research. Codes for various algorithms used in OR

eht-imaging. Imaging, analysis, and simulation software for radio interferometry

pytorch_GAN_zoo. A mix of GAN implementations including progressive growing

maskscoring_rcnn. Codes for paper "Mask Scoring R-CNN".

awesome-ai-safety. A curated list of awesome AI safety papers, projects and communities.

DANet. Dual Attention Network for Scene Segmentation (CVPR2019)

inpainting_gmcnn. Image Inpainting via Generative Multi-column Convolutional Neural Networks, NeurIPS2018

awesome-object-detection. Awesome Object Detection based on handong1587 github: https://handong1587.github.io/deep_learning/2015/10/09/object-detection.html

Easy-Ipm-Client. An easy, interface friendly cross-platform client to generate bird's view images using inverse perspective mapping methods proposed in paper "Adaptive Inverse Perspective Mapping for Lane Map Generation with SLAM"

GANotebooks. wgan, wgan2(improved, gp), infogan, and dcgan implementation in lasagne, keras, pytorch

PyTorch-Tutorials. Learn to build your neural network using PyTorch

CatterPlots. Did you ever wish you could make scatter plots with cat shaped points? Now you can!

box-convolutions. PyTorch code for the "Deep Neural Networks with Box Convolutions" paper

PlotNeuralNet. Latex code for making neural networks diagrams

deeptraffic. DeepTraffic is a deep reinforcement learning competition, part of the MIT Deep Learning series.

PixelAnnotationTool. Annotate quickly images.

ImageNet-Adversarial-Training. ImageNet classifier with state-of-the-art adversarial robustness

SSD-variants. PyTorch implementation of several SSD based object detection algorithms.

simpledet. A Simple and Versatile Framework for Object Detection and Instance Recognition

spear. Library for benchmarking adversarial defence methods.

Reinforcement_learning_tutorial_with_demo. Reinforcement Learning Tutorial with Demo: DP (Policy and Value Iteration), Monte Carlo, TD Learning (SARSA, QLearning), Function Approximation, Policy Gradient, DQN, Imitation, Meta Learning, Papers, Courses, etc..

holodeck. High Fidelity Simulator for Reinforcement Learning and Robotics Research.

nevergrad. A Python toolbox for performing gradient-free optimization

dilated. Smoothed Dilated Convolutions for Improved Dense Prediction

word-benchmarks. Benchmarks for intrinsic word embeddings evaluation.

state-of-the-art-result-for-machine-learning-problems. This repository provides state of the art (SoTA) results for all machine learning problems. We do our best to keep this repository up to date. If you do find a problem's SoTA result is out of date or missing, please raise this as an issue or submit Google form (with this information: research paper name, dataset, metric, source code and year). We will fix it immediately.

pytorch-examples. Simple examples to introduce PyTorch

FaderNetworks. Fader Networks: Manipulating Images by Sliding Attributes - NIPS 2017

vel. Velocity in deep-learning research

FewShot_GAN-Unet3D. Tensorflow implementation of our paper: Few-shot 3D Multi-modal Medical Image Segmentation using Generative Adversarial Learning

matplotlib-cpp. Extremely simple yet powerful header-only C++ plotting library built on the popular matplotlib

OtsuPyre. Blazingly Fast Approximation of Otsu's Multi-threshold Method

Interview-Bit. Solutions to problems on Interview Bit

stargan. StarGAN - Official PyTorch Implementation (CVPR 2018)

A-to-Z-Resources-for-Students. ✅ Curated list of resources for developers

Reinforcement-Learning. Learn Deep Reinforcement Learning in 60 days! Lectures & Code in Python. Reinforcement Learning + Deep Learning

awesome-adversarial-machine-learning. A curated list of awesome adversarial machine learning resources

adaptive-filters. My collection of implementations of adaptive filters.

interview. Interview questions

Image_deionising_auto_encoder. Noise removal from images using Convolutional autoencoder

Searching-for-activation-functions. NIPS Implementation challenge 2017 for "Searching for activation functions" paper by Google Brain

pytorch-semseg. Semantic Segmentation Architectures Implemented in PyTorch

NoisyNaturalGradient. Pytorch Implementation of paper "Noisy Natural Gradient as Variational Inference"

tensorflow-GANs. 各类GAN综合在一起，借鉴了hwalsuklee大神的

3D-Deepbox. 3D Bounding Box Estimation Using Deep Learning and Geometry (MultiBin)

3D-Machine-Learning. A resource repository for 3D machine learning

Dilation-Pytorch-Semantic-Segmentation. A PyTorch implementation of semantic segmentation according to Multi-Scale Context Aggregation by Dilated Convolutions by Yu and Koltun.

py-spy. Sampling profiler for Python programs

matplotlib_for_papers. Handout for the tutorial "Creating publication-quality figures with matplotlib"

PyTorch-GAN. PyTorch implementations of Generative Adversarial Networks.

baby-a3c. A high-performance Atari A3C agent in 180 lines of PyTorch

importance-sampling. Code for experiments regarding importance sampling for training neural networks

KalmanFilter. This is a Kalman filter used to calculate the angle, rate and bias from from the input of an accelerometer/magnetometer and a gyroscope.

vid2vid. Pytorch implementation of our method for high-resolution (e.g. 2048x1024) photorealistic video-to-video translation.

polyrnn-pp-pytorch. PyTorch training/tool code for Polygon-RNN++ (CVPR 2018)

ERP-BDAY. get birth date of your friend from ERP

generative-adversarial-networks. Introduction to generative adversarial networks, with code to accompany the O'Reilly tutorial on GANs

3D-ResNets-PyTorch. 3D ResNets for Action Recognition (CVPR 2018)

ganhacks. starter from "How to Train a GAN?" at NIPS2016

simple-faster-rcnn-pytorch. A simplified implemention of Faster R-CNN that replicate performance from origin paper

open-source-rover. A build-it-yourself, 6-wheel rover based on the rovers on Mars!

tensorflow_input_image_by_tfrecord. Feed your own image data to a pre-trained network by tensorflow

FPN_Tensorflow. A Tensorflow implementation of FPN detection framework.

awesome-robotics-libraries. :sunglasses: A curated list of robotics libraries and software

IGVC_Lane_Detector. Lane Detector and Navigator for IGVC 2018

self-driving-car. Udacity Self-Driving Car Engineer Nanodegree projects.

pytorch-semantic-segmentation. PyTorch for Semantic Segmentation

ResNetCAM-keras. Keras implementation of a ResNet-CAM model

Kalman-and-Bayesian-Filters-in-Python. Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.

Adventures-in-deep-learning. A curated list of Deep Learning resources sorted by reputation

tf-rnn-attention. Tensorflow implementation of attention mechanism for text classification tasks.

awesome-semantic-segmentation. :metal: awesome-semantic-segmentation

albumentations. Fast and flexible image augmentation library. Paper about the library: https://www.mdpi.com/2078-2489/11/2/125

academicpages.github.io. Github Pages template based upon HTML and Markdown for personal, portfolio-based websites.

build-your-own-x. Master programming by recreating your favorite technologies from scratch.

Automatic-Noun-Compound-Interpretation-using-Deep-Neural-Networks. Identification of semantic relation between constituents of a compound noun

Breast-Cancer-Detection. Code for breast cancer detection using single view and multi view ResNet 18

lanenet-lane-detection. Unofficial implemention of lanenet model for real time lane detection

Deep-Learning-Papers-Reading-Roadmap. Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!

image_captioning. Tensorflow implementation of "Show, Attend and Tell: Neural Image Caption Generation with Visual Attention"

pytorch-for-numpy-users. PyTorch for Numpy users. https://pytorch-for-numpy-users.wkentaro.com

Learning-to-See-in-the-Dark. Learning to See in the Dark. CVPR 2018

unet-pytorch. U-Net implementation for PyTorch based on https://arxiv.org/abs/1505.04597

mask_rcnn_ros. The ROS Package of Mask R-CNN for Object Detection and Segmentation

sonnet. TensorFlow-based neural network library

imgaug. Image augmentation for machine learning experiments.

FCN-pytorch. 🚘 Easiest Fully Convolutional Networks

pytorch-segmentation-detection. Image Segmentation and Object Detection in Pytorch

luminoth. Deep Learning toolkit for Computer Vision.

Mask_RCNN. Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow

spline. c++ cubic spline library

SLIC-Superpixels. Implementation of the SLIC superpixel algorithm to work with OpenCV

cheatsheets-ai. Essential Cheat Sheets for deep learning and machine learning researchers https://medium.com/@kailashahirwar/essential-cheat-sheets-for-machine-learning-and-deep-learning-researchers-efb6a8ebd2e5

Research-Internships-for-Undergraduates. Research internships + summer programs for undergraduate students worldwide (NASA, CERN, Max Planck, +100 more)

gym. A toolkit for developing and comparing reinforcement learning algorithms.

dlvcnptel. Tutorials for DLVC NPTEL MOOC

coding-interview-university. A complete computer science study plan to become a software engineer.

YOLOv3. Keras implementation of yolo v3 object detection.

tensorboard_logger. Log TensorBoard events without touching TensorFlow

Projects. :page_with_curl: A list of practical projects that anyone can solve in any programming language.

stanford-tensorflow-tutorials. This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.

python3_with_pleasure. A short guide on features of Python 3 with examples

AdversarialNetsPapers. Awesome paper list with code about generative adversarial nets

save-and-resume. Checkpoint tutorial on FloydHub for Pytorch, Keras and Tensorflow.

ann-visualizer. A python library for visualizing Artificial Neural Networks (ANN)

MacAdmins-2016-Craft-GUIs-with-Python-and-Tkinter. Code from my presentation for Penn State MacAdmins 2016

carbon. :black_heart: Create and share beautiful images of your source code

RL-Adventure. Pytorch Implementation of DQN / DDQN / Prioritized replay/ noisy networks/ distributional values/ Rainbow/ hierarchical RL

Practical_RL. A course in reinforcement learning in the wild

Halide. a language for fast, portable data-parallel computation

python-emotiv. A Python module to access Emotiv EPOC EEG headset on Linux.

livelossplot. Live training loss plot in Jupyter Notebook for Keras, PyTorch and others

awesome-blogs. Awesome blogs related to robotics, computer-vision, machine learning and much more

reinforcement-learning. Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.

mit-deep-learning-book-pdf. MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville

Awesome-CV. :page_facing_up: Awesome CV is LaTeX template for your outstanding job application