📈 Adaptive: parallel active learning of mathematical functions
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Updated
Sep 18, 2024 - Python
📈 Adaptive: parallel active learning of mathematical functions
Slimmable Networks, AutoSlim, and Beyond, ICLR 2019, and ICCV 2019
ST-SSL (STSSL): Spatio-Temporal Self-Supervised Learning for Traffic Flow Forecasting/Prediction
TensorFlow Eager implementation of NEAT and Adaptive HyperNEAT
🪁 A fast Adaptive Machine Learning library for Time-Series, that lets you build, deploy and update composite models easily. An order of magnitude speed-up, combined with flexibility and rigour. This is an internal project - documentation is not updated anymore and substantially differ from the current API.
A Python tool for 3D adaptive binary space partitioning and beyond
Partially Adaptive Momentum Estimation method in the paper "Closing the Generalization Gap of Adaptive Gradient Methods in Training Deep Neural Networks" (accepted by IJCAI 2020)
Run many functions (adaptively) on many cores (>10k-100k) using mpi4py.futures, ipyparallel, loky, or dask-mpi. 🎉
Codebase for the paper "adaptive deep reinforcement learning approach for MIMO PID control of mobile robots"
[Biomedical Signal Processing and Control] ECGTransForm: Empowering adaptive ECG arrhythmia classification framework with bidirectional transformer
A python framework to run adaptive Markov state model (MSM) simulation on HPC resources
DASP the Durham Adaptive optics Simulation Platform: Modelling and simulation of adaptive optics systems
Content-adaptive storage and processing of large volumetric microscopy data using the Adaptive Particle Representation (APR)
Virtual Reference Feedback Tuning (VRFT) Python Library - Alessio Russo (alessior@kth.se)
Wrap up Platform to launch all PELE features. [AdaptivePELE, MSM, LigandGrowing, Glide Rescoring]
Official Repository for the paper "Feature Extraction for Generative Medical Imaging Evaluation: New Evidence Against an Evolving Trend".
Code for FLEX, a fast, adaptive and flexible model-based reinforcement learning exploration algorithm.
Experimental code: adaptive importance sampling for bayesian networks.
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