261 Open source projects that are alternatives of or similar to LSM

Diverse, Noisy and Parallel: a New Spiking Neural Network Approach for Humanoid Robot Control

No description or website provided.

spiking-neural-networks

Code for Reservoir computing (Echo state network)

bitcoin prediction algorithms

My bachelor's thesis—analyzing the application of LSTM-based RNNs on financial markets. 🤓

A simple open domain generative based chatbot based on Recurrent Neural Networks

🌳 A tiny skiplist based log-structured merge-tree written in Rust.

Speaker Diarization is the problem of separating speakers in an audio. There could be any number of speakers and final result should state when speaker starts and ends. In this project, we analyze given audio file with 2 channels and 2 speakers (on separate channels).

Advanced file format fuzzer based-on deep neural language models.

Code snippets and solutions for the Introduction to Deep Learning and Neural Networks Course hosted in educative.io

Event-Based Angular Velocity Regression with Spiking Networks

Sequence analyzing using Recurrent Neural Networks (RNN) based on Keras

finance

Implementation of a Spiking Neural Network in Tensorflow.

Using LSTM network for time series forecasting

Code and Data to accompany "Dilated Convolutions for Modeling Long-Distance Genomic Dependencies", presented at the ICML 2017 Workshop on Computational Biology

Ordered Neurons LSTM

This repo provides projects on deep-learning mainly using Tensorflow 2.0

Simple (but often Strong) Baselines for POMDPs in PyTorch - ICML 2022

Malicious URL detector using keras recurrent networks and scikit-learn classifiers

💬 Recurrent neural network -- generates messages in your style of speech! Trained on imessage data. Sqlite3, TensorFlow, Flask, Twilio SMS, AWS.

JAX-based Spiking Neural Network framework

Deep-learning model presented in "DataStories at SemEval-2017 Task 6: Siamese LSTM with Attention for Humorous Text Comparison".

Deep learning for spiking neural networks

Official code for UnICORNN (ICML 2021)

A variational implementation of classical and quantum annealing using recurrent neural networks for the purpose of solving optimization problems.

NeuroAI-UW seminar, a regular weekly seminar for the UW community, organized by NeuroAI Shlizerman Lab.

Simulation of spiking neural networks (SNNs) using PyTorch.

The complete code and notebooks used for the ACM Recommender Systems Challenge 2019

도서 "핸즈온 머신러닝"의 예제와 연습문제를 담은 주피터 노트북입니다.

Sequence Segmentation using Joint RNN and Structured Prediction Models (ICASSP 2017)

OpenN@S: Open-source software to NAS automatic VHDL code generation

[AAAI 2020] Modeling Personality with Attentive Networks and Contextual Embeddings

Synaptic Plasticity with Online Reinforcement learning

Tensorflow implementation of "Tracking the World State with Recurrent Entity Networks" [https://arxiv.org/abs/1612.03969] by Henaff, Weston, Szlam, Bordes, and LeCun.

Using a recurrent neural network in TensorFlow to predict national origin by last name.

Auryn: A fast simulator for spiking neural networks with synaptic plasticity

Source code for "Transferring the Style of Homophonic Music Using Recurrent Neural Networks and Autoregressive Model"

This repository will host models, modules, algorithms and applications developed by the INRC Community to run on the Intel Loihi Platform.

Embeddable key-value database engine in pure TypeScript, based on LSM-Tree

One-Shot Object Appearance Learning using Spiking Neural Networks

Moore Machine Networks (MMN): Learning Finite-State Representations of Recurrent Policy Networks

Cloud-native Runtime Security Enforcement System

Sequence Labeling in Tensorflow

Entirety.ai Intuition to Implementation Meetup Content.

Storage algorithms.

Assignmends done for Udacity's Deep Learning MOOC with Vincent Vanhoucke

Brain Dynamics Programming in Python

A Python-Tensorflow neural network for classifying cancer data

Human activity recognition using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six categories (WALKING, WALKING_UPSTAIRS, WALKING_DOWNSTAIRS, SITTING, STANDING, LAYING).

Gathers Tensorflow deep learning models.

Implement Differentiable Architecture Search (DARTS) for RNN with fastai

RBM implemented with spiking neurons in Python. Contrastive Divergence used to train the network.

a deep recurrent model for exchangeable data

A robot learning from demonstration framework that trains a recurrent neural network for autonomous task execution

This repository contains my solutions to the assignments for Stanford's CS231n "Convolutional Neural Networks for Visual Recognition" (Spring 2020).

This is a STORN (Stochastical Recurrent Neural Network) implementation for keras!

Keras Implementation and Experiments with Deep Recurrent Neural Networks for Source Separation

Deep Learning using Rectified Linear Units (ReLU)