102 Repositories
Python experiments Libraries
learning and feeling SLAM together with hands-on-experiments
modern-slam-tutorial-python Learning and feeling SLAM together with hands-on-experiments 😀 😃 😆 Dependencies Most of the examples are based on GTSAM
The LaTeX and Python code for generating the paper, experiments' results and visualizations reported in each paper is available (whenever possible) in the paper's directory
This repository contains the software implementation of most algorithms used or developed in my research. The LaTeX and Python code for generating the
The starter repository for submissions to the GeneDisco challenge for optimized experimental design in genetic perturbation experiments
GeneDisco ICLR-22 Challenge Starter Repository The starter repository for submissions to the GeneDisco challenge for optimized experimental design in
Repo for my Tensorflow/Keras CV experiments. Mostly revolving around the Danbooru20xx dataset
SW-CV-ModelZoo Repo for my Tensorflow/Keras CV experiments. Mostly revolving around the Danbooru20xx dataset Framework: TF/Keras 2.7 Training SQLite D
This repository contains python code necessary to replicated the experiments performed in our paper "Invariant Ancestry Search"
InvariantAncestrySearch This repository contains python code necessary to replicated the experiments performed in our paper "Invariant Ancestry Search
Code for reproducible experiments presented in KSD Aggregated Goodness-of-fit Test.
Code for KSDAgg: a KSD aggregated goodness-of-fit test This GitHub repository contains the code for the reproducible experiments presented in our pape
Python-experiments - A Repository which contains python scripts to automate things and make your life easier with python
Python Experiments A Repository which contains python scripts to automate things
PyTorch framework, for reproducing experiments from the paper Implicit Regularization in Hierarchical Tensor Factorization and Deep Convolutional Neural Networks
Implicit Regularization in Hierarchical Tensor Factorization and Deep Convolutional Neural Networks. Code, based on the PyTorch framework, for reprodu
This repository contains code to run experiments in the paper "Signal Strength and Noise Drive Feature Preference in CNN Image Classifiers."
Signal Strength and Noise Drive Feature Preference in CNN Image Classifiers This repository contains code to run experiments in the paper "Signal Stre
repro_eval is a collection of measures to evaluate the reproducibility/replicability of system-oriented IR experiments
repro_eval repro_eval is a collection of measures to evaluate the reproducibility/replicability of system-oriented IR experiments. The measures were d
This is the source code for the experiments related to the paper Unsupervised Audio Source Separation Using Differentiable Parametric Source Models
Unsupervised Audio Source Separation Using Differentiable Parametric Source Models This is the source code for the experiments related to the paper Un
This is an open solution to the Home Credit Default Risk challenge 🏡
Home Credit Default Risk: Open Solution This is an open solution to the Home Credit Default Risk challenge 🏡 . More competitions 🎇 Check collection
Google AI Open Images - Object Detection Track: Open Solution
Google AI Open Images - Object Detection Track: Open Solution This is an open solution to the Google AI Open Images - Object Detection Track 😃 More c
Image Classification - A research on image classification and auto insurance claim prediction, a systematic experiments on modeling techniques and approaches
A research on image classification and auto insurance claim prediction, a systematic experiments on modeling techniques and approaches
Some experiments with tennis player aging curves using Hilbert space GPs in PyMC. Only experimental for now.
NOTE: This is still being developed! Setup notes This document uses Jeff Sackmann's tennis data. You can obtain it as follows: git clone https://githu
Experiments for Fake News explainability project
fake-news-explainability Experiments for fake news explainability project This repository only contains the notebooks used to train the models and eva
Logistic Bandit experiments. Official code for the paper "Jointly Efficient and Optimal Algorithms for Logistic Bandits".
Code for the paper Jointly Efficient and Optimal Algorithms for Logistic Bandits, by Louis Faury, Marc Abeille, Clément Calauzènes and Kwang-Sun Jun.
A Java implementation of the experiments for the paper "k-Center Clustering with Outliers in Sliding Windows"
OutliersSlidingWindows A Java implementation of the experiments for the paper "k-Center Clustering with Outliers in Sliding Windows" Dataset generatio
A PyTorch implementation of the continual learning experiments with deep neural networks
Brain-Inspired Replay A PyTorch implementation of the continual learning experiments with deep neural networks described in the following paper: Brain
Experiments for Operating Systems Lab (ETCS-352)
Operating Systems Lab (ETCS-352) Experiments for Operating Systems Lab (ETCS-352) performed by me in 2021 at uni. All codes are written by me except t
List of papers, code and experiments using deep learning for time series forecasting
Deep Learning Time Series Forecasting List of state of the art papers focus on deep learning and resources, code and experiments using deep learning f
Code and Experiments for ACL-IJCNLP 2021 Paper Mind Your Outliers! Investigating the Negative Impact of Outliers on Active Learning for Visual Question Answering.
Code and Experiments for ACL-IJCNLP 2021 Paper Mind Your Outliers! Investigating the Negative Impact of Outliers on Active Learning for Visual Question Answering.
Client - 🔥 A tool for visualizing and tracking your machine learning experiments
Weights and Biases Use W&B to build better models faster. Track and visualize all the pieces of your machine learning pipeline, from datasets to produ
Minimal diffusion models - Minimal code and simple experiments to play with Denoising Diffusion Probabilistic Models (DDPMs)
Minimal code and simple experiments to play with Denoising Diffusion Probabilist
PyTorch Lightning + Hydra. A feature-rich template for rapid, scalable and reproducible ML experimentation with best practices. ⚡🔥⚡
Lightning-Hydra-Template A clean and scalable template to kickstart your deep learning project 🚀 ⚡ 🔥 Click on Use this template to initialize new re
Minimal implementation and experiments of "No-Transaction Band Network: A Neural Network Architecture for Efficient Deep Hedging".
No-Transaction Band Network: A Neural Network Architecture for Efficient Deep Hedging Minimal implementation and experiments of "No-Transaction Band N
Scientific measurement library for instruments, experiments, and live-plotting
PyMeasure scientific package PyMeasure makes scientific measurements easy to set up and run. The package contains a repository of instrument classes a
Learning and experimenting with Kubernetes
Kubernetes Experiments This repository contains code that I'm using to learn and experiment with Kubernetes. 1. Environment setup minikube kubectl doc
Experiments with Tox plugin system
The project is an attempt to add to the tox some missing out of the box functionality. Basically it is just an extension for the tool that will be loa
Test scripts etc. for experimental rollup testing
rollup node experiments Test scripts etc. for experimental rollup testing. untested, work in progress python -m venv venv source venv/bin/activate #
Distributed behavioral experiments
Autopilot Docs Paper Forum Hardware Autopilot is a Python framework for performing complex, hardware-intensive behavioral experiments with swarms of n
This repo contains code to reproduce all experiments in Equivariant Neural Rendering
Equivariant Neural Rendering This repo contains code to reproduce all experiments in Equivariant Neural Rendering by E. Dupont, M. A. Bautista, A. Col
Codes for building and training the neural network model described in Domain-informed neural networks for interaction localization within astroparticle experiments.
Domain-informed Neural Networks Codes for building and training the neural network model described in Domain-informed neural networks for interaction
Flow is a computational framework for deep RL and control experiments for traffic microsimulation.
Flow Flow is a computational framework for deep RL and control experiments for traffic microsimulation. See our website for more information on the ap
Experiments on continual learning from a stream of pretrained models.
Ex-model CL Ex-model continual learning is a setting where a stream of experts (i.e. model's parameters) is available and a CL model learns from them
A lightweight, pure-Python mobile robot simulator designed for experiments in Artificial Intelligence (AI) and Machine Learning, especially for Jupyter Notebooks
aitk.robots A lightweight Python robot simulator for JupyterLab, Notebooks, and other Python environments. Goals A lightweight mobile robotics simulat
Experiments and examples converting Transformers to ONNX
Experiments and examples converting Transformers to ONNX This repository containes experiments and examples on converting different Transformers to ON
Experiments for Neural Flows paper
Neural Flows: Efficient Alternative to Neural ODEs [arxiv] TL;DR: We directly model the neural ODE solutions with neural flows, which is much faster a
Code to reproduce experiments in the paper "Task-Oriented Dialogue as Dataflow Synthesis" (TACL 2020).
Code to reproduce experiments in the paper "Task-Oriented Dialogue as Dataflow Synthesis" (TACL 2020).
Experiments with the Robust Binary Interval Search (RBIS) algorithm, a Query-Based prediction algorithm for the Online Search problem.
OnlineSearchRBIS Online Search with Best-Price and Query-Based Predictions This is the implementation of the Robust Binary Interval Search (RBIS) algo
HTSeq is a Python library to facilitate processing and analysis of data from high-throughput sequencing (HTS) experiments.
HTSeq DEVS: https://github.com/htseq/htseq DOCS: https://htseq.readthedocs.io A Python library to facilitate programmatic analysis of data from high-t
Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
Sacred Every experiment is sacred Every experiment is great If an experiment is wasted God gets quite irate Sacred is a tool to help you configure, or
PyTorch Implementation of DSB for Score Based Generative Modeling. Experiments managed using Hydra.
Diffusion Schrödinger Bridge with Applications to Score-Based Generative Modeling This repository contains the implementation for the paper Diffusion
Gin provides a lightweight configuration framework for Python
Gin Config Authors: Dan Holtmann-Rice, Sergio Guadarrama, Nathan Silberman Contributors: Oscar Ramirez, Marek Fiser Gin provides a lightweight configu
When BERT Plays the Lottery, All Tickets Are Winning
When BERT Plays the Lottery, All Tickets Are Winning Large Transformer-based models were shown to be reducible to a smaller number of self-attention h
A general framework for deep learning experiments under PyTorch based on pytorch-lightning
torchx Torchx is a general framework for deep learning experiments under PyTorch based on pytorch-lightning. TODO list gan-like training wrapper text
This is the official repository of the paper Stocastic bandits with groups of similar arms (NeurIPS 2021). It contains the code that was used to compute the figures and experiments of the paper.
Experiments How to reproduce experimental results of Stochastic bandits with groups of similar arms submitted paper ? Section 5 of the paper To reprod
Experiments with Fourier layers on simulation data.
Factorized Fourier Neural Operators This repository contains the code to reproduce the results in our NeurIPS 2021 ML4PS workshop paper, Factorized Fo
Automatically align face images 🙃→🙂. Can also do windowing and warping.
Automatic Face Alignment (AFA) Carl M. Gaspar & Oliver G.B. Garrod You have lots of photos of faces like this: But you want to line up all of the face
InfiniteBoost: building infinite ensembles with gradient descent
InfiniteBoost Code for a paper InfiniteBoost: building infinite ensembles with gradient descent (arXiv:1706.01109). A. Rogozhnikov, T. Likhomanenko De
How to use TensorLayer
How to use TensorLayer While research in Deep Learning continues to improve the world, we use a bunch of tricks to implement algorithms with TensorLay
Source code and notebooks to reproduce experiments and benchmarks on Bias Faces in the Wild (BFW).
Face Recognition: Too Bias, or Not Too Bias? Robinson, Joseph P., Gennady Livitz, Yann Henon, Can Qin, Yun Fu, and Samson Timoner. "Face recognition:
NLP and Text Generation Experiments in TensorFlow 2.x / 1.x
Code has been run on Google Colab, thanks Google for providing computational resources Contents Natural Language Processing(自然语言处理) Text Classificati
Code and experiments for "Deep Neural Networks for Rank Consistent Ordinal Regression based on Conditional Probabilities"
corn-ordinal-neuralnet This repository contains the orginal model code and experiment logs for the paper "Deep Neural Networks for Rank Consistent Ord
🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.
Image Super-Resolution (ISR) The goal of this project is to upscale and improve the quality of low resolution images. This project contains Keras impl
Contains an implementation (sklearn API) of the algorithm proposed in "GENDIS: GEnetic DIscovery of Shapelets" and code to reproduce all experiments.
GENDIS GENetic DIscovery of Shapelets In the time series classification domain, shapelets are small subseries that are discriminative for a certain cl
Calling Julia from Python - an experiment on data loading
Calling Julia from Python - an experiment on data loading See the slides. TLDR After reading Patrick's blog post, we decided to try to replace C++ wit
Repository containing detailed experiments related to the paper "Memotion Analysis through the Lens of Joint Embedding".
Memotion Analysis Through The Lens Of Joint Embedding This repository contains the experiments conducted as described in the paper 'Memotion Analysis
Supplementary code for the experiments described in the 2021 ISMIR submission: Leveraging Hierarchical Structures for Few Shot Musical Instrument Recognition.
Music Trees Supplementary code for the experiments described in the 2021 ISMIR submission: Leveraging Hierarchical Structures for Few Shot Musical Ins
A framework for using LSTMs to detect anomalies in multivariate time series data. Includes spacecraft anomaly data and experiments from the Mars Science Laboratory and SMAP missions.
Telemanom (v2.0) v2.0 updates: Vectorized operations via numpy Object-oriented restructure, improved organization Merge branches into single branch fo
ModelChimp is an experiment tracker for Deep Learning and Machine Learning experiments.
ModelChimp What is ModelChimp? ModelChimp is an experiment tracker for Deep Learning and Machine Learning experiments. ModelChimp provides the followi
Experiments in converting wikidata to ftm
FollowTheMoney / Wikidata mappings This repo will contain tools for converting Wikidata entities into FtM schema. Prefixes: https://www.mediawiki.org/
Code & Experiments for "LILA: Language-Informed Latent Actions" to be presented at the Conference on Robot Learning (CoRL) 2021.
LILA LILA: Language-Informed Latent Actions Code and Experiments for Language-Informed Latent Actions (LILA), for using natural language to guide assi
A sandpit for textual related things
A sandpit repo for testing textual related things.
Official codebase for "B-Pref: Benchmarking Preference-BasedReinforcement Learning" contains scripts to reproduce experiments.
B-Pref Official codebase for B-Pref: Benchmarking Preference-BasedReinforcement Learning contains scripts to reproduce experiments. Install conda env
reproduces experiments from
Installation To enable importing of modules, from the parent directory execute: pip install -e . To install requirements: python -m pip install requir
A toolset for creating Qualtrics-based IAT experiments
Qualtrics IAT Tool A web app for generating the Implicit Association Test (IAT) running on Qualtrics Online Web App The app is hosted by Streamlit, a
Official codebase for "B-Pref: Benchmarking Preference-BasedReinforcement Learning" contains scripts to reproduce experiments.
B-Pref Official codebase for B-Pref: Benchmarking Preference-BasedReinforcement Learning contains scripts to reproduce experiments. Install conda env
Experiments and code to generate the GINC small-scale in-context learning dataset from "An Explanation for In-context Learning as Implicit Bayesian Inference"
GINC small-scale in-context learning dataset GINC (Generative In-Context learning Dataset) is a small-scale synthetic dataset for studying in-context
The code for replicating the experiments from the LFI in SSMs with Unknown Dynamics paper.
Likelihood-Free Inference in State-Space Models with Unknown Dynamics This package contains the codes required to run the experiments in the paper. Th
This repository is dedicated to developing and maintaining code for experiments with wide neural networks.
Wide-Networks This repository contains the code of various experiments on wide neural networks. In particular, we implement classes for abc-parameteri
TensorFlow Metal Backend on Apple Silicon Experiments (just for fun)
tf-metal-experiments TensorFlow Metal Backend on Apple Silicon Experiments (just for fun) Setup This is tested on M1 series Apple Silicon SOC only. Te
OpenGL experiments with Pygame & ModernGL
pygame-opengl OpenGL experiments with Pygame & ModernGL TODO Skybox & Reflections Post-process effects (motion blur, color correction, etc..) Normal m
This is the repo for the paper "Improving the Accuracy-Memory Trade-Off of Random Forests Via Leaf-Refinement".
Improving the Accuracy-Memory Trade-Off of Random Forests Via Leaf-Refinement This is the repository for the paper "Improving the Accuracy-Memory Trad
PsychoPy is an open-source package for creating experiments in behavioral science.
PsychoPy is an open-source package for creating experiments in behavioral science. It aims to provide a single package that is: precise enoug
Code to reproduce the experiments from our NeurIPS 2021 paper " The Limitations of Large Width in Neural Networks: A Deep Gaussian Process Perspective"
Code To run: python runner.py new --save SAVE_NAME --data PATH_TO_DATA_DIR --dataset DATASET --model model_name [options] --n 1000 - train - t
Code for reproducing experiments in "Improved Training of Wasserstein GANs"
Improved Training of Wasserstein GANs Code for reproducing experiments in "Improved Training of Wasserstein GANs". Prerequisites Python, NumPy, Tensor
TorchOk - The toolkit for fast Deep Learning experiments in Computer Vision
TorchOk - The toolkit for fast Deep Learning experiments in Computer Vision
Experiments for distributed optimization algorithms
Network-Distributed Algorithm Experiments -- This repository contains a set of optimization algorithms and objective functions, and all code needed to
XManager: A framework for managing machine learning experiments 🧑🔬
XManager is a platform for packaging, running and keeping track of machine learning experiments. It currently enables one to launch experiments locally or on Google Cloud Platform (GCP). Interaction with experiments is done via XManager's APIs through Python launch scripts.
PyTorch code to run synthetic experiments.
Code repository for Invariant Risk Minimization Source code for the paper: @article{InvariantRiskMinimization, title={Invariant Risk Minimization}
Code to reproduce experiments in the paper "Explainability Requires Interactivity".
Explainability Requires Interactivity This repository contains the code to train all custom models used in the paper Explainability Requires Interacti
PyTorch implementation of the supervised learning experiments from the paper Model-Agnostic Meta-Learning (MAML)
pytorch-maml This is a PyTorch implementation of the supervised learning experiments from the paper Model-Agnostic Meta-Learning (MAML): https://arxiv
Experiments on Flood Segmentation on Sentinel-1 SAR Imagery with Cyclical Pseudo Labeling and Noisy Student Training
Flood Detection Challenge This repository contains code for our submission to the ETCI 2021 Competition on Flood Detection (Winning Solution #2). Acco
PyTorch experiments with the Zalando fashion-mnist dataset
zalando-pytorch PyTorch experiments with the Zalando fashion-mnist dataset Project Organization ├── LICENSE ├── Makefile - Makefile with co
PyTorch Personal Trainer: My framework for deep learning experiments
Alex's PyTorch Personal Trainer (ptpt) (name subject to change) This repository contains my personal lightweight framework for deep learning projects
A collection of interactive machine-learning experiments: 🏋️models training + 🎨models demo
🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo
Random Erasing Data Augmentation. Experiments on CIFAR10, CIFAR100 and Fashion-MNIST
Random Erasing Data Augmentation =============================================================== black white random This code has the source code for
Experiments with differentiable stacks and queues in PyTorch
Please use stacknn-core instead! StackNN This project implements differentiable stacks and queues in PyTorch. The data structures are implemented in s
Neural implicit reconstruction experiments for the Vector Neuron paper
Neural Implicit Reconstruction with Vector Neurons This repository contains code for the neural implicit reconstruction experiments in the paper Vecto
Implementation of experiments in the paper Clockwork Variational Autoencoders (project website) using JAX and Flax
Clockwork VAEs in JAX/Flax Implementation of experiments in the paper Clockwork Variational Autoencoders (project website) using JAX and Flax, ported
This repository contains the implementations related to the experiments of a set of publicly available datasets that are used in the time series forecasting research space.
TSForecasting This repository contains the implementations related to the experiments of a set of publicly available datasets that are used in the tim
Code to run experiments in SLOE: A Faster Method for Statistical Inference in High-Dimensional Logistic Regression.
Code to run experiments in SLOE: A Faster Method for Statistical Inference in High-Dimensional Logistic Regression. Not an official Google product. Me
Algorithmic trading with deep learning experiments
Deep-Trading Algorithmic trading with deep learning experiments. Now released part one - simple time series forecasting. I plan to implement more soph
Code to reproduce the experiments in the paper "Transformer Based Multi-Source Domain Adaptation" (EMNLP 2020)
Transformer Based Multi-Source Domain Adaptation Dustin Wright and Isabelle Augenstein To appear in EMNLP 2020. Read the preprint: https://arxiv.org/a
Image augmentation for machine learning experiments.
imgaug This python library helps you with augmenting images for your machine learning projects. It converts a set of input images into a new, much lar
L2X - Code for replicating the experiments in the paper Learning to Explain: An Information-Theoretic Perspective on Model Interpretation.
L2X Code for replicating the experiments in the paper Learning to Explain: An Information-Theoretic Perspective on Model Interpretation at ICML 2018,
ReproZip is a tool that simplifies the process of creating reproducible experiments from command-line executions, a frequently-used common denominator in computational science.
ReproZip ReproZip is a tool aimed at simplifying the process of creating reproducible experiments from command-line executions, a frequently-used comm
Simple reimplemetation experiments about FcaNet
FcaNet-CIFAR An implementation of the paper FcaNet: Frequency Channel Attention Networks on CIFAR10/CIFAR100 dataset. how to run Code: python Cifar.py
Applications using the GTN library and code to reproduce experiments in "Differentiable Weighted Finite-State Transducers"
gtn_applications An applications library using GTN. Current examples include: Offline handwriting recognition Automatic speech recognition Installing