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Implementation of Classifier Free Guidance in Pytorch, with emphasis on text conditioning, and flexibility to include multiple text embedding models
Approaching (Almost) Any Machine Learning Problem
Visualize/test models for visual representation by synthesizing images.
PyTorch implementation of Bootstrap Your Own Latent: A New Approach to Self-Supervised Learning
Discrete-time Signal Processing 3rd edition (Oppenheim)
🦖Pytorch implementation of popular Attention Mechanisms, Vision Transformers, MLP-Like models and CNNs.🔥🔥🔥
Recurrent Switching Linear Dynamical Systems
AI & parametric QR code generator. AI & 参数化二维码生成器。https://qrbtf.com
This repository is part of a "Machine Learning from Scratch" seminar at Harvard Medical School.
Rebuild the Stable Diffusion Model in a single python script. Tutorial for Harvard ML from Scratch Series
A series of tutorial notebooks on denoising diffusion probabilistic models in PyTorch
A simple tutorial of wavelet, STFT and FFT
🥚 EnerGy Guided Diffusion for optimizing neurally exciting images
Python Kalman filtering and optimal estimation library. Implements Kalman filter, particle filter, Extended Kalman filter, Unscented Kalman filter, g-h (alpha-beta), least squares, H Infinity, smoo…
An Implementation of SVM - Support Vector Machines using Linear Kernel. This is just for understanding of SVM and its algorithm.
Basic soft-margin kernel SVM implementation in Python
MNIST digit classification with scikit-learn and Support Vector Machine (SVM) algorithm.
🎉 Elegant and powerful theme for Hexo.
OpenScope databook: a collaborative, versioned, data-centric collection of foundational analyses for reproducible systems neuroscience 🐁🧠🔬🖥️📈
Collecting research materials on EBM/EBL (Energy Based Models, Energy Based Learning)
A lightweight and flexible framework for Hebbian learning in PyTorch.
paper lists and information on mean-field theory of deep learning
Using the Monte Carlo methods in problem solving.
Introduction to classical Monte Carlo methods
PyTorch implementation of Neural Processes
Reinforcement Learning Tutorial with Demo: DP (Policy and Value Iteration), Monte Carlo, TD Learning (SARSA, QLearning), Function Approximation, Policy Gradient, DQN, Imitation, Meta Learning, Pape…
A minimal, responsive, and feature-rich Jekyll theme for technical writing.