AI’s Memorization Crisis

O n Tuesday, researchers at Stanford and Yale revealed something that AI companies would prefer to keep hidden. Four popular ...

Deep learning creates virtual multiplexed immunostaining to improve cancer diagnosis

Researchers at the University of California, Los Angeles (UCLA), in collaboration with pathologists from Hadassah Hebrew ...
Deep Learning with Yacine on MSNOpinion

How to train LLMs with long context

Learn how to train large language models (LLMs) effectively with long context inputs. Techniques, examples, and tips included ...
Daily Excelsior

Machine Learning Methods Used for Portfolio Optimization and Risk Management

Machine learning is reshaping the way portfolios are built, monitored, and adjusted. Investors are no longer limited to ...

AI river forecasts may be accurate, but based on flawed logic

Artificial intelligence is changing how we predict river flow—but a new study led by researchers at the University of British ...
Scientific Research Publishing

Li, W. and Becker, D.M. (2021) Day-Ahead Electricity Price Prediction Applying Hybrid Models of LSTM-Based Deep Learning Methods and Feature Selection Algorithms under ...

ABSTRACT: Accurate forecasting of the system marginal price (SMP) is crucial to improve demand-side management and optimize power generation scheduling. However, predicting the SMP is challenging due ...
Frontiers

A physical state prediction method based on reduce order model and deep learning applied in virtual reality

The application of virtual reality (VR) in industrial training and safety emergency needs to reflect realistic changes in physical object properties. However, existing VR systems still lack fast and ...
Frontiers

Intelligent maneuver decision-making for UAVs using the TD3–LSTM reinforcement learning algorithm under uncertain information

Aiming to address the complexity and uncertainty of unmanned aerial vehicle (UAV) aerial confrontation, a twin delayed deep deterministic policy gradient (TD3)–long short-term memory (LSTM) ...
C&EN

SOH Estimation Based on Multisource Feature Extraction and SSA-LSTM Algorithm

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. In contrast, data-driven methods do not rely on fixed models or ...
IEEE

Enhancing Creativity and Validation in Explanatory Deep Learning-Based Symbolic Music Generation: A Hybrid Approach With LSTM and Genetic Algorithms

Abstract: This research proposes an explanatory deep learning-based music generation approach, where the output of a deep learning model is validated through a set of predefined musical rules, with a ...