Official code repository for the publication "Latent Equilibrium: A unified learning theory for arbitrarily fast computation with arbitrarily slow neurons"

Overview

Latent Equilibrium: A unified learning theory for arbitrarily fast computation with arbitrarily slow neurons

This repository contains the code to reproduce the results of the NeurIPS 2021 submission "Latent Equilibrium: A unified learning theory for arbitrarily fast computation with arbitrarily slow neurons" (also available on arXiv).

Requirements

To install requirements:

pip install -r requirements.txt

Training & Evaluation

Code for FC MNIST experiments (Fig.2b and 4ac)

The code can be found in fig2b_fig4ac_mnist/src/.

Running the experiments: For example, in order to run all the experiments needed to reproduce Fig. 2b, execute:

cd fig2b_fig4ac_mnist/src/
/bin/bash 2b_jobs.sh

The results of each run, that is for example metrics, output and configurations, will be saved in fig2b_fig4ac_mnist/runs/{run_number}/.

For the experiment in Fig.4 replace 2b_jobs.sh with 4a_jobs.sh or 4c_jobs.sh respectively

The seeds chosen for these experiments were 42 69 12345 98765 38274 28374 42848 48393 83475 57381.

Code for HIGGS, MNIST and CIFAR10 with and without LE (Fig. 2cde).

The code can be found in fig2cde_higgs_mnist_cifar10.

The code configuration is integrated into the main files and only a few parameters are configured via argparse.

To run the code, check the respective submit_python_*_v100.sh file which contains examples and all run configurations for all seeds used.

The seeds chosen for these experiments were 1, 2, 3, 5, 7, 8, 13, 21, 34. (Fibonacci + lucky number 7), resulting in 9 seeds for each experiment.

Results can be found in the respective log file produced from the std out of the running code via python -u *_training.py > file.log.

Code for Dendritic Microcircuits with and without LE (Fig.3 and 5)

The code can be found in fig3fig5_dendritic_microcircuits/src/.

The experiments are configured using config files. All config files required for the production of the plotted results are in fig3fig5_dendritic_microcircuits/experiment_configs/. The naming scheme of the config files is as follows {task name}_{with LE or not}_tpres_{tpres in unit dt}.yaml where task name is bars (Fig.3) or mimic (Fig.5) and with LE or not is either le or orig.

For each run the results will be saved in fig3fig5_dendritic_microcircuits/experiment_results/{config file name}_{timestamp}/.

To run an experiment:

cd fig3fig5_dendritic_microcircuits/src/
python3 run_bars.py train ../experiment_configs/{chosen_config_file}

For the experiment in Fig.5 replace run_bars.py with run_single_mc.py

To plot the results of a run:

cd fig3fig5_dendritic_microcircuits/src/
python3 run_bars.py eval ../experiment_results/{results_dir_of_run_to_be_evaluated}

This will generate plots of the results (depending on how many variables you configured to be recorded, more or less plots can be generated) and save them in the respective results directory. Which plots are plotted is defined in run_X.py

Reproduce all data needed for Fig3:

For the results shown in Fig.3 all config files with the name bars_*.yaml need to be run for 10 different seeds (configurable in the config file). The seeds chosen for these experiments were 12345, 12346, 12347, 12348, 12349, 12350, 12351, 12352, 12353, 12354.

Contributing

📋 TODO: Pick a licence and describe how to contribute to your code repository.

Owner
Computational Neuroscience, University of Bern
Computational Neuroscience, University of Bern
Code release for NeuS

NeuS We present a novel neural surface reconstruction method, called NeuS, for reconstructing objects and scenes with high fidelity from 2D image inpu

Peng Wang 813 Jan 04, 2023
Real time sign language recognition

The proposed work aims at converting american sign language gestures into English that can be understood by everyone in real time.

Mohit Kaushik 6 Jun 13, 2022
SEAN: Image Synthesis with Semantic Region-Adaptive Normalization (CVPR 2020, Oral)

SEAN: Image Synthesis with Semantic Region-Adaptive Normalization (CVPR 2020 Oral) Figure: Face image editing controlled via style images and segmenta

Peihao Zhu 579 Dec 30, 2022
Simulating an AI playing 2048 using the Expectimax algorithm

2048-expectimax Simulating an AI playing 2048 using the Expectimax algorithm The base game engine uses code from here. The AI player is modeled as a m

Subha Ramesh 2 Jan 31, 2022
StellarGraph - Machine Learning on Graphs

StellarGraph Machine Learning Library StellarGraph is a Python library for machine learning on graphs and networks. Table of Contents Introduction Get

S T E L L A R 2.6k Jan 05, 2023
Seach Losses of our paper 'Loss Function Discovery for Object Detection via Convergence-Simulation Driven Search', accepted by ICLR 2021.

CSE-Autoloss Designing proper loss functions for vision tasks has been a long-standing research direction to advance the capability of existing models

Peidong Liu(刘沛东) 54 Dec 17, 2022
Resilient projection-based consensus actor-critic (RPBCAC) algorithm

Resilient projection-based consensus actor-critic (RPBCAC) algorithm We implement the RPBCAC algorithm with nonlinear approximation from [1] and focus

Martin Figura 5 Jul 12, 2022
This repository contains the code for the paper in EMNLP 2021: "HRKD: Hierarchical Relational Knowledge Distillation for Cross-domain Language Model Compression".

HRKD: Hierarchical Relational Knowledge Distillation for Cross-domain Language Model Compression This repository contains the code for the paper in EM

Chenhe Dong 2 Mar 24, 2022
An implementation of a sequence to sequence neural network using an encoder-decoder

Keras implementation of a sequence to sequence model for time series prediction using an encoder-decoder architecture. I created this post to share a

Luke Tonin 195 Dec 17, 2022
Code for the paper "Learning-Augmented Algorithms for Online Steiner Tree"

Learning-Augmented Algorithms for Online Steiner Tree This is the code for the paper "Learning-Augmented Algorithms for Online Steiner Tree". Requirem

0 Dec 09, 2021
Torchlight2 lan game server tool - A message forwarding tool for Torchlight 2 lan game

Torchlight 2 Lan Game Server Tool A message forwarding tool for Torchlight 2 lan

Huaijun Jiang 3 Nov 01, 2022
Open-source python package for the extraction of Radiomics features from 2D and 3D images and binary masks.

pyradiomics v3.0.1 Build Status Linux macOS Windows Radiomics feature extraction in Python This is an open-source python package for the extraction of

Artificial Intelligence in Medicine (AIM) Program 842 Dec 28, 2022
Exploring Visual Engagement Signals for Representation Learning

Exploring Visual Engagement Signals for Representation Learning Menglin Jia, Zuxuan Wu, Austin Reiter, Claire Cardie, Serge Belongie and Ser-Nam Lim C

Menglin Jia 9 Jul 23, 2022
Semi-Supervised 3D Hand-Object Poses Estimation with Interactions in Time

Semi Hand-Object Semi-Supervised 3D Hand-Object Poses Estimation with Interactions in Time (CVPR 2021).

96 Dec 27, 2022
MADE (Masked Autoencoder Density Estimation) implementation in PyTorch

pytorch-made This code is an implementation of "Masked AutoEncoder for Density Estimation" by Germain et al., 2015. The core idea is that you can turn

Andrej 498 Dec 30, 2022
FinGAT: A Financial Graph Attention Networkto Recommend Top-K Profitable Stocks

FinGAT: A Financial Graph Attention Networkto Recommend Top-K Profitable Stocks This is our implementation for the paper: FinGAT: A Financial Graph At

Yu-Che Tsai 64 Dec 13, 2022
Human4D Dataset tools for processing and visualization

HUMAN4D: A Human-Centric Multimodal Dataset for Motions & Immersive Media HUMAN4D constitutes a large and multimodal 4D dataset that contains a variet

tofis 15 Nov 09, 2022
Experiments for Fake News explainability project

fake-news-explainability Experiments for fake news explainability project This repository only contains the notebooks used to train the models and eva

Lorenzo Flores (Lj) 1 Dec 03, 2022
The official homepage of the (outdated) COCO-Stuff 10K dataset.

COCO-Stuff 10K dataset v1.1 (outdated) Holger Caesar, Jasper Uijlings, Vittorio Ferrari Overview Welcome to official homepage of the COCO-Stuff [1] da

Holger Caesar 263 Dec 11, 2022
OpenVINO黑客松比赛项目

Window_Guard OpenVINO黑客松比赛项目 英文名称:Window_Guard 中文名称:窗口卫士 硬件 树莓派4B 8G版本 一个磁石开关 USB摄像头(MP4视频文件也可以) 软件(库) OpenVINO RPi 使用方法 本项目使用的OPenVINO是是2021.3版本,并使用了

Tango 6 Jul 04, 2021