Jev Gamper

OpenEDM-wire-tensioner. [OpenEDM] Wire Tensioner Project

OpenEDM-arc-generator. [OpenEDM] Arc Generator Project

de-news. AI news app in simple German

MicroManipulatorStepper. A sub-micrometer 3D motion control plattform.

minimo. Learning Formal Mathematics from Intrinsic Motivation

openMotor. An open-source internal ballistics simulator for rocket motor experimenters

RocketPy. Next generation High-Power Rocketry 6-DOF Trajectory Simulation

open_vins. An open source platform for visual-inertial navigation research.

seqGAN. A simplified PyTorch implementation of "SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient." (Yu, Lantao, et al.)

SeqGAN. Implementation of Sequence Generative Adversarial Nets with Policy Gradient

MambaViT. ViT architecture with Mamba instead of transformer backbone

GeoGen. Automated generation of planar geometry olympiad problems

intrinsic-dimensionality. Use this package to compute intrinsic dimensionality of your task given a fixed neural network in PYTORCH! :fire:

py-safestats. Python

QuantReg.jl. An implementation of quantile regression for Julia modeled after the R quantreg package.

tree-of-thought-llm. [NeurIPS 2023] Tree of Thoughts: Deliberate Problem Solving with Large Language Models

LIPP. Testing Local Independence in Point Processes

causaltransportr. R package to generalize and transport causal effects.

logisticPCA. Dimensionality reduction for binary data

SCMMAB-NIPS2018. Structural Causal Bandit

NeuralSymbolicRegressionThatScales. Source code and Dataset creation for the paper "Neural Symbolic Regression That Scales"

transformers-lego. Python

statsforecast. Lightning ⚡️ fast forecasting with statistical and econometric models.

BeautifulAlgorithms.jl. Concise and beautiful algorithms written in Julia

Agents.jl. Agent-based modeling framework in Julia

WGT-Literature. Literature for Women Go Tech exercises

tufte_algorithms_book. A template for textbooks in the same style as Algorithms for Optimization

phdthesis. Gaussian Processes and Statistical Decision-making in Non-Euclidean Spaces

Javis.jl. Julia Animations and Visualizations

mixtureSPRT. Package for mixture sequential probability ratio test

A-Simulation-Study-on-A-B-Testing. See the code and conclusion of a review of common challenges that emerge while conducting an A/B test

abayes. Simulate Bayesian A/B testing algorithms and evaluate the results of A/B tests with a shiny app.

diplomacy_searchbot. Code to accompany "Human-Level Performance in No-Press Diplomacy via Equilibrium Search", published at ICLR 2021

rl-diplomacy-challenge. The repository for the Diplomacy game Reinforcement Learning challenge

manim-tweets. Code for tweets by @manim_community on twitter

drconfseq. Doubly robust confidence sequences for sequential causal inference

manim. A community-maintained Python framework for creating mathematical animations.

quince. Code for Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding

realcause. Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed causal structure.

torchdiffeq. Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.

neural_stpp. Deep generative modeling for time-stamped heterogeneous data, enabling high-fidelity models for a large variety of spatio-temporal domains.

clv-cdnow. Modelling Customer Lifetime Value on CDNOW dataset

glom-pytorch. An attempt at the implementation of Glom, Geoffrey Hinton's new idea that integrates concepts from neural fields, top-down-bottom-up processing, and attention (consensus between columns), for emergent part-whole heirarchies from data

TGP.pytorch. Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021

BTYDplus. R package for Customer Behavior Analysis

lifetimes. Lifetime value in Python

abcpy. ABCpy package

bpemb. Pre-trained subword embeddings in 275 languages, based on Byte-Pair Encoding (BPE)

synbols. The Synbols dataset generator is a ServiceNow Research project that was started at Element AI.

CausalBayesianOptimization. Code for the Causal Bayesian Optimization algorithm (http://proceedings.mlr.press/v108/aglietti20a/aglietti20a.pdf)

multiverse. MultiVerse: Probabilistic Programming Language for Causal Reasoning

disentanglement. Official repository for our ICLR 2021 paper Evaluating the Disentanglement of Deep Generative Models with Manifold Topology

RepVGG. RepVGG: Making VGG-style ConvNets Great Again

Music-diversity-measures. Spotify project to create and test various diversity measures

markov-chain. Jupyter Notebook

zr-obp. Open Bandit Pipeline: a python library for bandit algorithms and off-policy evaluation

ddlk. Deep direct likelihood knockoffs

pml-book. "Probabilistic Machine Learning" - a book series by Kevin Murphy

recommenders. Best Practices on Recommendation Systems

open_stt. Open STT

drnet. 💉📈 Dose response networks (DRNets) are a method for learning to estimate individual dose-response curves for multiple parametric treatments from observational data using neural networks.

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.

causalml. Uplift modeling and causal inference with machine learning algorithms

aciccomp. Code to run submissions for the Atlantic Causal Inference Competition

causalAI. The open source repository for the Causal Modeling in Machine Learning Workshop at Altdeep.ai @ www.altdeep.ai/courses/causalAI

legere-coetus-chartam. What does Cervest's science team read during it's reading group?

CEVAE-pyro. CEVAE(Causal Effect Variational AutoEncoder) written with pytorch and pyro.

causal_inference_python_code. Python code for part 2 of the book Causal Inference: What If, by Miguel Hernán and James Robins

ucate. Uncertainty in Conditional Average Treatment Effect Estimation

pubmed_parser. :clipboard: A Python Parser for PubMed Open-Access XML Subset and MEDLINE XML Dataset

pdfminer.six. Community maintained fork of pdfminer - we fathom PDF

pypdf. A pure-python PDF library capable of splitting, merging, cropping, and transforming the pages of PDF files

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

swiftForTensorFlowWorkshop. This workshop covers the swift for TensorFlow python interoperability and trains a model entirely in swift and then uses it in an IOS App.

slurm-for-ml. A Machine Learning workflow for Slurm.

NuClick. Interactive Segmentation of Nucleus

gpumonitor. TF 2.x and PyTorch Lightning Callbacks for GPU monitoring

SegLossOdyssey. A collection of loss functions for medical image segmentation

cleanlab. Cleanlab's open-source library is the standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

excalidraw. Virtual whiteboard for sketching hand-drawn like diagrams

S_CellDetect_Stardist_HE_ROI. Cell (Nuclei) Detection in ROI using Stardist

emo_2013_viz. Codebase for EMO 2013 visualisation paper "Visualising high-dimensional Pareto relationships in two-dimensional scatterplots, Evolutionary Multi-criterion Optimization" by Fieldsend & Everson

CLAM. Open source tools for computational pathology - Nature BME

self-label. Self-labelling via simultaneous clustering and representation learning. (ICLR 2020)

gan-sandbox. Play around with GANs

hovernet_inference. HoVer-Net inference code for simultaneous nuclear segmentation and classification

toma. Helps you write algorithms in PyTorch that adapt to the available (CUDA) memory

markdown-cv. a simple template to write your CV in a readable markdown file and use CSS to publish/print it.

SensorEffectAugmentation. This repository contains the code used in the work Modeling Camera Effects to Improve Visual Learning from Synthetic Data (https://arxiv.org/abs/1803.07721)

imcmc. Image Markov Chain Monte Carlo

doccano. Open source annotation tool for machine learning practitioners.

fax. Python

CoordConv-pytorch. Pytorch implementation of CoordConv introduced in 'An intriguing failing of convolutional neural networks and the CoordConv solution' paper. (https://arxiv.org/pdf/1807.03247.pdf)

code-for-Generalization-properties-of-neural-networks-trained-on-Lorenz-systems. Python

WeatherBench. A benchmark dataset for data-driven weather forecasting

robust_representations. Code for "Learning Perceptually-Aligned Representations via Adversarial Robustness"

pytorch-checkpoint. Python

rl_a3c_pytorch. A3C LSTM Atari with Pytorch plus A3G design

spectral-metric. Code for the CVPR 2019 paper : Spectral Metric for Dataset Complexity Assessment

pipreqs. pipreqs - Generate pip requirements.txt file based on imports of any project. Looking for maintainers to move this project forward.

CKA-Centered-Kernel-Alignment. Reproduce CKA: Similarity of Neural Network Representations Revisited

attention-sampling. This Python package enables the training and inference of deep learning models for very large data, such as megapixel images, using attention-sampling

Lottery-Ticket-Hypothesis-in-Pytorch. This repository contains a Pytorch implementation of the paper "The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks" by Jonathan Frankle and Michael Carbin that can be easily adapted to any model/dataset.

sparse_learning. Sparse learning library and sparse momentum resources.

loss-landscape. Code for visualizing the loss landscape of neural nets

optuna. A hyperparameter optimization framework

climt. The official home of climt, a Python based climate modelling toolkit.

grobid-client-python. Python client for GROBID Web services

MultiObjectiveOptimization. Source code for Neural Information Processing Systems (NeurIPS) 2018 paper "Multi-Task Learning as Multi-Objective Optimization"

intrinsic-dimensionality. PyTorch Implementation of CVPR'19 - On the Intrinsic Dimensionality of Image Representation

FIGR. Few-shot Image Generation with Reptile

tika-python. Tika-Python is a Python binding to the Apache Tika™ REST services allowing Tika to be called natively in the Python community.

cca.pytorch. CCAs for looking into DNNs

academic. Jekyll theme with a focus on simplicity, typography and flexibility

al-folio. A beautiful, simple, clean, and responsive Jekyll theme for academics

pytorch-hed. a reimplementation of Holistically-Nested Edge Detection in PyTorch

tvm. Open deep learning compiler stack for cpu, gpu and specialized accelerators

cayman. Cayman is a Jekyll theme for GitHub Pages

bi-tempered-loss. Robust Bi-Tempered Logistic Loss Based on Bregman Divergences. https://arxiv.org/pdf/1906.03361.pdf

lifelike. WIP predicted survival functions

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

deep-neural-decision-forests. A model combining Deep Neural Networks and (Stochastic) Random Forests.

fully-differentiable-deep-ndf-tf. Fully differentiable deep-neural decision forest in tensorflow

Neural-Decision-Forests. An implementation of the Deep Neural Decision Forests in PyTorch

pytube. Lightweight, dependency-free Python library and CLI for downloading YouTube videos, playlists, and captions.

forecast_rodeo. Python

MT-net. Code accompanying the ICML-2018 paper "Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace"

ICML-2019-Weakly-Supervised-Temporal-Localization-via-Occurrence-Count-Learning. Python

sparsemax-pytorch. Implementation of Sparsemax activation in Pytorch

Deep-SAD-PyTorch. A PyTorch implementation of Deep SAD, a deep Semi-supervised Anomaly Detection method.

set_transformer. Pytorch implementation of set transformer

TILAb-Score. This repository contains the implementation of TILAb-score as described in the original paper.

meta-dataset. A dataset of datasets for learning to learn from few examples

nnet-survival. Discrete-Time Survival Model for Neural Networks

bigdata18. Transfer learning for time series classification

partialconv. A New Padding Scheme: Partial Convolution based Padding

IIC. Invariant Information Clustering for Unsupervised Image Classification and Segmentation

TCN. Sequence modeling benchmarks and temporal convolutional networks

cocostuff. The official homepage of the COCO-Stuff dataset.

cocostuff10k. The official homepage of the (outdated) COCO-Stuff 10K dataset.

self-tuning-networks. Code for Self-Tuning Networks (ICLR 2019) https://arxiv.org/abs/1903.03088

clearml. ClearML - Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline, Orchestration, Scheduling & Serving in one MLOps/LLMOps solution

associative_deep_clustering. Jupyter Notebook

PySyft. Perform data science on data that remains in someone else's server

Finished_Senior_LSC_Python. Python implementation of LSC algorithm, (C) Zhengqin Li, Jiansheng Chen, 2014

py3nvml. Python 3 Bindings for NVML library. Get NVIDIA GPU status inside your program.

pymgrs. Pure Python MGRS coordinate converter.

alibi. Algorithms for explaining machine learning models

MTLCC-pytorch. A pytorch implementation of the (Tensorflow) MTLCC network implementation

cloudless. Deep learning pipeline for orbital satellite data for detecting clouds

RevGAN. RevGAN implementation in PyTorch. We extend the Pix2pix and CycleGAN framework by exploring approximately invertible architectures in 2D and 3D. These architectures are approximately invertible by design and thus partially satisfy cycle-consistency before training even begins. Furthermore, since invertible architectures have constant memory complexity in depth, these models can be built arbitrarily deep without requiring additional memory. In the paper we demonstrate superior quantitative output on the Cityscapes and Maps datasets at near constant memory budget.

eo-learn. Earth observation processing framework for machine learning in Python

woody. A Python library for random forests

pyshp. This library reads and writes ESRI Shapefiles in pure Python.

Python-Numerics. Numerical machines in Python

Eidolon. Eidolons: Novel Stimuli for Vision Research

STSC. Self-Tuning Spectral Clustering Python

raster-vision. An open source library and framework for deep learning on satellite and aerial imagery.

Bayesian-CycleGAN. [TNNLS] Bayesian Cycle-Consistent Generative Adversarial Networks via Marginalizing Latent Sampling

automl_gpu. Python

set-transformer. A neural network architecture for prediction on sets

fully-invertible-revnet. Python

BNPSeg. Bayesian Non-Parametric Image Segmentation using HDP-MRF

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.

AttentionExplanation. Jupyter Notebook

goxmeans. An implementation of the x-means algorithm in Go.

pyclustering. pyclustering is a Python, C++ data mining library.

pyxmeans. Quick implementation of xmeans in python and C

biobert. Bioinformatics'2020: BioBERT: a pre-trained biomedical language representation model for biomedical text mining

TextTopicNet. Self-supervised learning of visual features through embedding images into text topic spaces

beauvoir. Domain randomization library in Python for object detection and classification using Blender.

pytorch_compact_bilinear_pooling. Compact Bilinear Pooling for PyTorch

Deep-SVDD-PyTorch. A PyTorch implementation of the Deep SVDD anomaly detection method

pdffigures2. Given a scholarly PDF, extract figures, tables, captions, and section titles.

pdffigures. Command line tool to extract figures, tables, and captions from scholarly documents in PDF form.

rev. REV: Reverse-Engineering Visualizations

scatteract. Project which implements extraction of data from scatter plots

FigureQA. Python

svcca. Jupyter Notebook

pcse. Repository for the Python Crop Simulation Environment

one-shot-texture-segmentation. Code to generate data used in One-shot Texture Segmentation paper

noise-as-targets-tensorflow. Noise-as-targets representation learning for cifar10. Implementation based on the paper "Unsupervised Learning by Predicting Noise" by Bojanowski and Joulin.

fair_noise_as_targets. Implementation of the Unsupervised learning by predicting noise paper

RoBO. RoBO: a Robust Bayesian Optimization framework

deepcluster. Deep Clustering for Unsupervised Learning of Visual Features

AdaBound. An optimizer that trains as fast as Adam and as good as SGD.

SpectralNet. Deep network that performs spectral clustering

tencent-ml-images. Largest multi-label image database; ResNet-101 model; 80.73% top-1 acc on ImageNet

lossgrad. Implementation of the LOSSGRAD optimization algorithm

HBP-pytorch. Hierarchical Bilinear Pooling for Fine-Grained Visual Recognition reimplement in Pytorch.

Pytorch-Utils. Useful functions to work with PyTorch. At the moment, there is a function to work with cross validation and kernels visualization.

CompactBilinearPooling-Pytorch. A Pytorch Implementation for Compact Bilinear Pooling.

versa. Code to reproduce experiments in "Meta-learning probabilistic inference for prediction"

HowToTrainYourMAMLPytorch. The original code for the paper "How to train your MAML" along with a replication of the original "Model Agnostic Meta Learning" (MAML) paper in Pytorch.

BMAML. Re-implement of Bayesian Model-Agnostic Meta-Learning

swa_gaussian. Code repo for "A Simple Baseline for Bayesian Uncertainty in Deep Learning"

models. Models and examples built with TensorFlow

DeepLearningSurvival. PyTorch implementation of Deep Survival Models.

point_process_optimisation. Efficient point process inference for large scale object detection

deepslide. Code for the Nature Scientific Reports paper "Pathologist-level classification of histologic patterns on resected lung adenocarcinoma slides with deep neural networks." A sliding window framework for classification of high resolution whole-slide images, often microscopy or histopathology images.