AZoOptics

Researchers Design AI-Driven Photonic Crystal Fiber Modulator

A deep reinforcement learning framework optimizes silicon-based photonic crystal fiber modulators, achieving ultra-low ...

Measuring process over product: AI approach assesses learning processes

Artificial intelligence (AI) is profoundly reshaping education worldwide. While AI tools increasingly support students in ...
IEEE Spectrum on MSN

AI is designing radio chips that humans couldn’t even imagine

Freed from intelligibility and aesthetics, AI designs faster ...
AHA/ASA Journals

Contrastive Machine Learning to Quantify Hypertensive Multiorgan Damage and Identify New Disease Phenotypes: A Multinational Multimodal Study

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...
IEEE

Off-Dynamics Inverse Reinforcement Learning

Abstract: Imitation learning is a widely-used paradigm for decision making that learns from expert demonstrations. Existing imitation algorithms often require multiple interactions between the agent ...
Science Daily

Scientists reveal a hidden hormone switch for learning

Researchers uncovered how estrogen subtly reshapes learning by strengthening dopamine reward signals in the brain. Rats learned faster when estrogen levels were high and struggled when the hormone’s ...
New York Post

Doctors are calling ‘inverse vaccines’ the ‘holy grail’ for fighting diseases like MS and celiac

A revolutionary treatment for autoimmune diseases could be on the horizon. Twenty-four million to 50 million Americans have an autoimmune disease, in which the body’s immune system mistakenly attacks ...
IEEE

Curricular Subgoals for Inverse Reinforcement Learning

Abstract: Inverse Reinforcement Learning (IRL) aims to reconstruct the reward function from expert demonstrations to facilitate policy learning, and has demonstrated its remarkable success in ...
C&EN

Machine Learning-Aided Inverse Design and Discovery of Novel Polymeric Materials for Membrane Separation

Global optimization tools such as Bayesian Optimization (BO) have also demonstrated their great potential in a variety of inverse design problems in materials engineering. (124) BO is an iterative ...