Official implementation of Score-CAM in PyTorch
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Updated
Aug 6, 2022 - Python
Official implementation of Score-CAM in PyTorch
My optimization(With and Without gradient) library
Code for FLEX, a fast, adaptive and flexible model-based reinforcement learning exploration algorithm.
Continuous domain Particle Swarm Optimization (PSO) with inertia weight decay and cognitive/social acceleration.
Continuous domain Particle Swarm Optimization (PSO) with inertia weight decay and cognitive/social acceleration.
Your language model forgets everything. Sillage gives it a 4 MB memory that persists across sessions, no gradients, no fine-tuning, no growing index. Beats an unbounded kNN-LM at 1/13 the storage (perplexity 31 → 17). CPU-only, fully reproducible, four preprints with Zenodo DOIs.
Fast runtime for Random Optimization at scale.
Similarity Differences and Uniqueness Explainable AI method
Tensorflow Optimizer using the SPSA method
This repo shows a MATLAB implementation of score-CAM (Wang et al., CVPR workshop, 2020). This method is the first gradient-free CAM-based visualization method for explaining CNN decision.
ADMM approach to train neural networks without gradient.
Repository containing code to run Score-CAM algorithm available on https://arxiv.org/pdf/1910.01279v1.pdf.
VRAXION public SDK and boundary docs for the private engine.
A Julia implementation of Simultaneous Perturbation Stochastic Approximation
Drift-Bounded Spectral Updates for Deep Local Learning
Gradient-free RL for LunarLander-v3 with population search, zeroth-order optimization, JAX, and parallel runs.
Visualizing 3D ResNet for Medical Image Classification With Score-CAM
Gradient-free neural network optimisation: PSO vs Adam vs SGD — from-scratch NumPy, 29-test suite, CI/CD
Deep neural network trained with Particle Swarm Optimization (gradient-free), with the dnnpso package and benchmarks
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