Mor Geva

EMBER-Embedding-Erasure. Official code for EMBER (EMBedding ERasure)

prime-rl. Agentic RL Training at Scale

decomposing-activations-local-geometry. Jupyter Notebook

hallucinated-reference-finder. Python

LMEnt. Python

circuit-tracer. Python

PISCES. 🪝PISCES - Precise In-Parameter Suppression for Concept EraSure in Large Language Models

arr-report-generator. This tool generates beautiful, interactive HTML reports for reviewing ARR submissions using OpenReview data.

MAPS. HTML

open-operator. Open-source resources on agents for computer use.

research-career-tools. Python

cookbook. Deep learning for dummies. All the practical details and useful utilities that go into working with real models.

GlobalProtect-openconnect. A GlobalProtect VPN client for Linux, written in Rust, based on OpenConnect and Tauri, supports SSO with MFA, YubiKey, and client certificate authentication, etc.

BIMT. Brain-Inspired Modular Training (BIMT), a method for making neural networks more modular and interpretable.

dangerous_dave. Dangerous Dave reverse engineering and level editing utility

wptools. Wikipedia tools (for Humans): easily extract data from Wikipedia, Wikidata, and other MediaWikis

GPU-Puzzles. Solve puzzles. Learn CUDA.

ml-pen-and-paper-exercises. Pen and paper exercises in machine learning

self-debiasing. This repository contains the code for "Self-Diagnosis and Self-Debiasing: A Proposal for Reducing Corpus-Based Bias in NLP".

contrast-sets. Python

strategyqa. The official code of TACL 2021, "Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategies".

learning_to_retrieve_reasoning_paths. The official implementation of ICLR 2020, "Learning to Retrieve Reasoning Paths over Wikipedia Graph for Question Answering".

wikiextractor. A tool for extracting plain text from Wikipedia dumps

allennlp-models. Officially supported AllenNLP models

golden-retriever. Authors' implementation of EMNLP-IJCNLP 2019 paper "Answering Complex Open-domain Questions Through Iterative Query Generation"

nlp_paper_summaries. ✍️ A carefully curated list of NLP paper summaries

hiplot. HiPlot makes understanding high dimensional data easy

suggestion. Google suggest API

knockknock. 🚪✊Knock Knock: Get notified when your training ends with only two additional lines of code

DROP-explorer. A data explorer for DROP dataset

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.

testSignificanceNLP. Python

MTMSN. A Multi-Type Multi-Span Network for Reading Comprehension that Requires Discrete Reasoning

spacy-wordnet. spacy-wordnet creates annotations that easily allow the use of wordnet and wordnet domains by using the nltk wordnet interface

amti. A Mechanical Turk Interface (amti) 🤖

drop-bert. NABERT model for solving the DROP dataset

GNNPapers. Must-read papers on graph neural networks (GNN)

spider-schema-gnn. Author implementation of the paper "Representing Schema Structure with Graph Neural Networks for Text-to-SQL Parsing"

pytorch_geometric. Graph Neural Network Library for PyTorch

self-attentive-parser. High-accuracy NLP parser with models for 11 languages.

dgl. Python package built to ease deep learning on graph, on top of existing DL frameworks.

pytorch-gated-graph-neural-network. A simple Pytorch implementation of Gated Graph Neural Networks

graph-based-deep-learning-literature. links to conference publications in graph-based deep learning

isect_segments-bentley_ottmann. BentleyOttmann sweep-line implementation (for finding all intersections in a set of line segments)

discofuse.

neuralcoref. ✨Fast Coreference Resolution in spaCy with Neural Networks

GraKeL. A scikit-learn compatible library for graph kernels

PlotNeuralNet. Latex code for making neural networks diagrams

edit-distance. Python library for computing edit distance between arbitrary Python sequences.

allennlp. An open-source NLP research library, built on PyTorch.

word-rnn-tensorflow. Multi-layer Recurrent Neural Networks (LSTM, RNN) for word-level language models in Python using TensorFlow.

nmt. TensorFlow Neural Machine Translation Tutorial

TF-Model-Service. Flask microservice of TensorFlow models

NeuroX-demo. JavaScript

e-SNLI. Python

AD3. Alternating Directions Dual Decomposition

sparsemap. SparseMAP: differentiable sparse structure inference

Sentiment-Analysis-based-on-Naive-Bayes-Adaboost. Python

neural-networks-and-deep-learning. Code samples for my book "Neural Networks and Deep Learning"

NLP-progress. Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.

naacl18tutorial. NAACL 2018 Tutorial: Modelling Natural Language, Programs, and their Intersection

smt. Statistical Machine Translation implementation with Python: especially IBM Model1, 2, and phrase-based machine translation.

nlp-datasets. Alphabetical list of free/public domain datasets with text data for use in Natural Language Processing (NLP)

models. Models and examples built with TensorFlow

caffe. Caffe: a fast open framework for deep learning.

cs231n.github.io. Public facing notes page

refdb. Stores paper references, outputs to bib/html, does basic sanity checking on bib entries

experiments_with_python. experiments with python

nlp_tasks. Natural Language Processing Tasks and References

fastText. Library for fast text representation and classification.

document-qa. Python

char-embeddings. A repository containing 300D character embeddings derived from the GloVe 840B/300D dataset, and uses these embeddings to train a deep learning model to generate Magic: The Gathering cards using Keras

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

tensor2tensor. Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.

DQN_DDQN_Dueling_and_DDPG_Tensorflow. Tensorflow + OpenAI Gym implementation of Deep Q-Network (DQN), Double DQN (DDQN), Dueling Network and Deep Deterministic Policy Gradient (DDPG)

DQN-tensorflow. Tensorflow implementation of Human-Level Control through Deep Reinforcement Learning

baselines. OpenAI Baselines: high-quality implementations of reinforcement learning algorithms

NLPH. The Vision and goals of the Open Natural Language Processing in Hebrew Project

gpu-burn. Microway's improved version of GPU Burn

tensorflow_cookbook. Code for Tensorflow Machine Learning Cookbook

tensorflow-community-wheels. Place to upload links to TensorFlow wheels

deep-RL. Deep Reinforcement Learning

homework. Assignments for CS294-112.

drl. Deep RL Algorithms implemented for UC Berkeley's CS 294-112: Deep Reinforcement Learning

awesome-hebrew-nlp. :book: A curated list of resources for NLP (Natural Language Processing) for Hebrew

stanford_corenlp_pywrapper. Java

RaSoR-in-Tensorflow. The implementation of one of the SQuAD solutions

RaSoR. Author implementation of "Learning Recurrent Span Representations for Extractive Question Answering" (Lee et al. 2016)

facets. Visualizations for machine learning datasets

rl4nlp. Reinforcement learning for natural language processing reading group

text-world-player. Framework and model code for the paper "Language Understanding for Text-based Games using Deep Reinforcement Learning", EMNLP 2015

DeepRL-Agents. A set of Deep Reinforcement Learning Agents implemented in Tensorflow.

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

mincemeatpy. Lightweight MapReduce in Python3

tensorflow. An Open Source Machine Learning Framework for Everyone

NLIWOD. Collection of tools, utilities, datasets and approaches towards realising natural language interfaces for the Web of Data.

labyrinth-algorithms. Explanation for various algorithms that are used for pathfinding.

Practical_RL. A course in reinforcement learning in the wild

ML. Python

Babler. Data Collection System For NLP/Speech Recognition

Reinforcement-Learning. Reinforcement Learning with TensorFlow

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

GloVe. Software in C and data files for the popular GloVe model for distributed word representations, a.k.a. word vectors or embeddings

papers. Summaries of machine learning papers

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

tf-dann. Domain-Adversarial Neural Network in Tensorflow

domain_adversarial_neural_network. Domain Adaptation Representation Learning Algorithm (as published in JMLR 2016)

multiNLI. Python

bi-att-flow. Bi-directional Attention Flow (BiDAF) network is a multi-stage hierarchical process that represents context at different levels of granularity and uses a bi-directional attention flow mechanism to achieve a query-aware context representation without early summarization.

TensorFlow-Examples. TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)

awesome-tensorflow. TensorFlow - A curated list of dedicated resources http://tensorflow.org

multiffn-nli. Implementation of the multi feed-forward network architecture by Parikh et al. (2016) for Natural Language Inference.

lectures. Oxford Deep NLP 2017 course

nlp-datasets. A list of datasets/corpora for NLP tasks, in reverse chronological order.

sempre. Semantic Parser with Execution

practical-pytorch. Go to https://github.com/pytorch/tutorials - this repo is deprecated and no longer maintained

dynet. DyNet: The Dynamic Neural Network Toolkit

fold. Deep learning with dynamic computation graphs in TensorFlow

awesome-public-datasets. A topic-centric list of HQ open datasets.

deep-learning-keras-tensorflow. Introduction to Deep Neural Networks with Keras and Tensorflow

ipython. Official repository for IPython itself. Other repos in the IPython organization contain things like the website, documentation builds, etc.

CLRS. :notebook:Solutions to Introduction to Algorithms