Showing 901-920 of 1,591 projects
A reinforcement learning environment based on the classic FPS game Doom, useful for AI and ML research.
Advanced Deep Learning with Keras book for learning deep learning concepts using the Keras framework
A reinforcement learning agent trained in a diffusion world model for AI research and development.
Official PyTorch implementation for a novel method to visualize classifications by Transformer based networks.
A Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization.
Instructions for setting up a deep learning development environment on your machine.
A computer vision library for training and deploying deep learning models, with support for popular datasets and tasks.
A flexible, free, and unlimited Python tool to translate between different languages using multiple translators.
A deep learning-powered invoice processing platform built with Python, Flask, and Keras/TensorFlow.
A curated list of deep learning applications in computational biology, useful for bioinformatics developers.
SAM is a PyTorch-based library that implements Sharpness-Aware Minimization, an optimization algorithm for training more robust deep learning models.
A Python toolkit for building machine/deep learning models on partially-observed time series data
A Python library for physical symbolic optimization, combining deep learning and reinforcement learning.
An ECCV 2022 paper on long-term video object segmentation using an Atkinson-Shiffrin memory model.
Pytorch implementations of various Bayesian neural network techniques for approximate inference and uncertainty quantification.
Deep learning model to analyze a large corpus of clear text passwords.
This is a tutorial on using deep learning for natural language processing with PyTorch.
An automatic evaluator for instruction-following language models with human-validated, high-quality, cheap, and fast evaluation.
A deep learning approach for password guessing and password strength analysis.
A Python library for learning and evaluating knowledge graph embeddings
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