Numenta published papers code and data

Overview

Numenta research papers code and data

This repository contains reproducible code for selected Numenta papers. It is currently under construction and will eventually include the source code for all the scripts used in Numenta's papers.

Grid Cell Path Integration For Movement-Based Visual Object Recognition

This paper demonstrates the implementation of a sensorimotor network that uses grid-cell computations to process a sequence of visual inputs, specifically a sequence of image patches from the MNIST dataset. The network is able to classify novel digits (as well as perform other tasks) in a way that is robust to the specific sequence over which the visual space is sampled, a challenging setting for typical machine learning approaches. The work builds on our previous paper, “Locations in the Neocortex."

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Going Beyond the Point Neuron: Active Dendrites and Sparse Representations for Continual Learning

In this paper we investigate how dendritic properties can add value to ANNs in the context of continual learning, an area where ANNs suffer from catastrophic forgetting

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How Can We Be So Dense? The Benefits of Using Highly Sparse Representations

In this paper we discuss inherent benefits of high dimensional sparse representations. We focus on robustness and sensitivity to interference. These are central issues with today’s neural network systems where even small and large perturbations can cause dramatic changes to a network’s output.

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Locations in the Neocortex: A Theory of Sensorimotor Object Recognition Using Cortical Grid Cells

This paper provides an implementation for a location layer with grid-like modules that encode object-specific locations. This layer is incorpated into a network with an input layer and simulations show how the model can learn many complex objects and later infer which learned object is being sensed.

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A Theory of How Columns in the Neocortex Enable Learning the Structure of the World

This paper proposes a network model composed of columns and layers that performs robust object learning and recognition. The model introduces a new feature to cortical columns, location information, which is represented relative to the object being sensed. Pairing sensory features with locations is a requirement for modeling objects and therefore must occur somewhere in the neocortex. We propose it occurs in every column in every region.

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The HTM Spatial Pooler – a neocortical algorithm for online sparse distributed coding

This paper describes an important component of HTM, the HTM spatial pooler, which is a neurally inspired algorithm that learns sparse distributed representations online. Written from a neuroscience perspective, the paper demonstrates key computational properties of HTM spatial pooler.

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Evaluating Real-time Anomaly Detection Algorithms - the Numenta Anomaly Benchmark

14th IEEE ICMLA 2015 - This paper discusses how we should think about anomaly detection for streaming applications. It introduces a new open-source benchmark for detecting anomalies in real-time, time-series data.

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Unsupervised Real-Time Anomaly Detection for Streaming Data

This paper discusses the requirements necessary for real-time anomaly detection in streaming data, and demonstrates how Numenta's online sequence memory algorithm, HTM, meets those requirements. It presents detailed results using the Numenta Anomaly Benchmark (NAB), the first open-source benchmark designed for testing real-time anomaly detection algorithms.

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Why Neurons Have Thousands of Synapses, A Theory of Sequence Memory in Neocortex

Foundational paper describing core HTM theory for sequence memory and its relationship to the neocortex. Written with a neuroscience perspective, the paper explains why neurons need so many synapses and how networks of neurons can form a powerful sequence learning mechanism.

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Owner
Numenta
Biologically inspired machine intelligence
Numenta
Consistency Regularization for Adversarial Robustness

Consistency Regularization for Adversarial Robustness Official PyTorch implementation of Consistency Regularization for Adversarial Robustness by Jiho

40 Dec 17, 2022
Code for the paper "Relation of the Relations: A New Formalization of the Relation Extraction Problem"

This repo contains the code for the EMNLP 2020 paper "Relation of the Relations: A New Paradigm of the Relation Extraction Problem" (Jin et al., 2020)

YYY 27 Oct 26, 2022
This package proposes simplified exporting pytorch models to ONNX and TensorRT, and also gives some base interface for model inference.

PyTorch Infer Utils This package proposes simplified exporting pytorch models to ONNX and TensorRT, and also gives some base interface for model infer

Alex Gorodnitskiy 11 Mar 20, 2022
Image restoration with neural networks but without learning.

Warning! The optimization may not converge on some GPUs. We've personally experienced issues on Tesla V100 and P40 GPUs. When running the code, make s

Dmitry Ulyanov 7.4k Jan 01, 2023
Tutorial for the PERFECTING FACTORY 5.0 WITH EDGE-POWERED AI workshop

Workshop Advantech Jetson Nano This tutorial has been designed for the PERFECTING FACTORY 5.0 WITH EDGE-POWERED AI workshop in collaboration with Adva

Edge Impulse 18 Nov 22, 2022
Pytorch implementation of paper "Learning Co-segmentation by Segment Swapping for Retrieval and Discovery"

SegSwap Pytorch implementation of paper "Learning Co-segmentation by Segment Swapping for Retrieval and Discovery" [PDF] [Project page] If our project

xshen 41 Dec 10, 2022
[ICCV 2021 Oral] Mining Latent Classes for Few-shot Segmentation

Mining Latent Classes for Few-shot Segmentation Lihe Yang, Wei Zhuo, Lei Qi, Yinghuan Shi, Yang Gao. This codebase contains baseline of our paper Mini

Lihe Yang 66 Nov 29, 2022
ONNX Runtime Web demo is an interactive demo portal showing real use cases running ONNX Runtime Web in VueJS.

ONNX Runtime Web demo is an interactive demo portal showing real use cases running ONNX Runtime Web in VueJS. It currently supports four examples for you to quickly experience the power of ONNX Runti

Microsoft 58 Dec 18, 2022
Live Hand Tracking Using Python

Live-Hand-Tracking-Using-Python Project Description: In this project, we will be

Hassan Shahzad 2 Jan 06, 2022
Coded illumination for improved lensless imaging

CodedCam Coded Illumination for Improved Lensless Imaging Paper | Supplementary results | Data and Code are available. Coded illumination for improved

Computational Sensing and Information Processing Lab 1 Nov 29, 2021
LaBERT - A length-controllable and non-autoregressive image captioning model.

Length-Controllable Image Captioning (ECCV2020) This repo provides the implemetation of the paper Length-Controllable Image Captioning. Install conda

bearcatt 53 Nov 13, 2022
Multi-Task Deep Neural Networks for Natural Language Understanding

New Release We released Adversarial training for both LM pre-training/finetuning and f-divergence. Large-scale Adversarial training for LMs: ALUM code

Xiaodong 2.1k Dec 30, 2022
code for EMNLP 2019 paper Text Summarization with Pretrained Encoders

PreSumm This code is for EMNLP 2019 paper Text Summarization with Pretrained Encoders Updates Jan 22 2020: Now you can Summarize Raw Text Input!. Swit

Yang Liu 1.2k Dec 28, 2022
PyBrain - Another Python Machine Learning Library.

PyBrain -- the Python Machine Learning Library =============================================== INSTALLATION ------------ Quick answer: make sure you

2.8k Dec 31, 2022
PiCIE: Unsupervised Semantic Segmentation using Invariance and Equivariance in clustering (CVPR2021)

PiCIE: Unsupervised Semantic Segmentation using Invariance and Equivariance in Clustering Jang Hyun Cho1, Utkarsh Mall2, Kavita Bala2, Bharath Harihar

Jang Hyun Cho 164 Dec 30, 2022
Robot Servers and Server Manager software for robo-gym

robo-gym-server-modules Robot Servers and Server Manager software for robo-gym. For info on how to use this package please visit the robo-gym website

JR ROBOTICS 4 Aug 16, 2021
Invariant Causal Prediction for Block MDPs

MISA Abstract Generalization across environments is critical to the successful application of reinforcement learning algorithms to real-world challeng

Meta Research 41 Sep 17, 2022
custom pytorch implementation of MoCo v3

MoCov3-pytorch custom implementation of MoCov3 [arxiv]. I made minor modifications based on the official MoCo repository [github]. No ViT part code an

39 Nov 14, 2022
Detecting and Tracking Small and Dense Moving Objects in Satellite Videos: A Benchmark

This dataset is a large-scale dataset for moving object detection and tracking in satellite videos, which consists of 40 satellite videos captured by Jilin-1 satellite platforms.

Qingyong 87 Dec 22, 2022
VM3000 Microphones

VM3000-Microphones This project was completed by Ricky Leman under the supervision of Dr Ben Travaglione and Professor Melinda Hodkiewicz as part of t

UWA System Health Lab 0 Jun 04, 2021