Machine learning workflow enables faster, more reliable organic crystal structure prediction

Prediction of crystal structures of organic molecules is a critical task in many industries, especially in pharmaceuticals ...
GitHub

Time series forecasting using LSTM-Neural-Networks

The primary objective was to design, train, and evaluate a three-layer LSTM model for accurate price prediction, using a dataset of minute-by-minute Bitcoin prices from January 1, 2021, to March 1, ...
IEEE

Short-Term Power Load Forecasting Under Unstable Data Quality: A Fuzzy Deep Neural Network With LSTM and Self-Attention

Abstract: This article presents a deep neural network model that integrates long short-term memory (LSTM), fuzzy logic, and self-attention mechanism to enhance short-term power load forecasting, ...
IEEE

Cross-LSTM: Integrating Cross Attention With Long Short-Term Memory Neural Networks in Estimating Joint Moments From Wearable Sensors

Abstract: Precise estimation of joint moments is essential for designing rehabilitation interventions and optimising the control of assistive devices. Current methods, including physics-based ...
Frontiers

Image steganalysis using LSTM fused convolutional neural networks for secure telemedicine

Deep learning-based image steganalysis has progressed in recent times, with efforts more concerted toward prioritizing detection accuracy over lightweight frameworks. In the context of AI-driven ...
Frontiers

Editorial: Deep neural network architectures and reservoir computing

Over the past decade, deep learning (DL) techniques such as convolutional neural networks (CNNs) and long short-term memory (LSTM) networks have played a pivotal role in advancing the field of ...
GitHub

mahmoud554377/bitcoin-price-prediction

This project explores and compares the effectiveness of different deep learning models for cryptocurrency price prediction. By analyzing historical Bitcoin data including OHLCV (Open, High, Low, Close ...
C&EN

Simulating Open Quantum Dynamics with a Neural Network-Enhanced Non-Markovian Stochastic Schrödinger Equation

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.jctc.5c00215. Derivation of cNMSSE; neural network architecture and ...
ascopubs.org

Performance analysis of artificial intelligence–driven convolutional neural network architectures for liver tumor segmentation.

Comparative efficacy and safety of donafenib versus bevacizumab in combination with immune checkpoint inhibitors and interventional therapy for advanced hepatocellular carcinoma: A retrospective ...
Science Daily

Energy and memory: A new neural network paradigm

Listen to the first notes of an old, beloved song. Can you name that tune? If you can, congratulations -- it's a triumph of your associative memory, in which one piece of information (the first few ...