The PASS dataset: pretrained models and how to get the data
- computer-vision
- self-supervised-learning
- representation-learning
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The PASS dataset: pretrained models and how to get the data
Pytorch framework for doing deep learning on point clouds.
Things we learned from Capture The Flag hacking competitions we participated in.
Embodied In-Context Learning for GPT-6 Astra
zoofs is a python library for performing feature selection using a variety of nature-inspired wrapper algorithms. The algorithms range from swarm-intelligence to physics-based to Evolutionary. It's easy to use , flexible and powerful tool to reduce your feature size.
Create adversarial attacks against machine learning Windows malware detectors
ROS package for the Perception (Sensor Processing, Detection, Tracking and Evaluation) of the KITTI Vision Benchmark Suite
INGInious is a secure and automated exercises assessment platform using your own tests, also providing a pluggable interface with your existing LMS.
Python-based implementations of algorithms for learning on imbalanced data.
A library for augmenting annotated audio data
Relevance Vector Machine implementation using the scikit-learn API.
The first exam for code agents in the physical world: frozen robot tasks from many benchmark suites, each answered with a program and verified in a separate sandbox. Runs on Harbor.
Automated 3D cell detection in very large images
A fast xgboost feature selection algorithm
Deep and Machine Learning for Microscopy
Stacked Generalization (Ensemble Learning)
The official implementation of "The Shapley Value of Classifiers in Ensemble Games" (CIKM 2021).
Companion repository for “In-Context Learning for Robots: Methods and Applications” — methods, datasets, and benchmarks organized by taxonomy and release date.
Deep Reinforcement Learning for Financial Trading using Price Trailing @ ICASSP 2019
:sunrise: A comprehensive, cutting-edge open-source framework for next-generation Transformers, with compute-matched benchmarking and a platform for autonomous architecture research.
BatchFlow helps you conveniently work with random or sequential batches of your data and define data processing and machine learning workflows even for datasets that do not fit into memory.
Meta Self-learning for Multi-Source Domain Adaptation: A Benchmark
PyTorch Connectomics: segmentation toolbox for EM connectomics
TranslatedAn agent development practice room based on LangGraph subgraphs: requirement clarification, user notes, document generation, and human review.