eLife

A differentiable model for optimizing the genetic drivers of synaptogenesis

This study presents SynaptoGen, a differentiable extension of connectome models that links gene expression, protein-protein interaction probabilities, synaptic multiplicity, and synaptic weights, and ...
Scientific Research Publishing

Reinforcement Learning for Antidepressant Dose Adjustment: An Explainable Agent Approach ()

Reinforcement Learning, Explainable AI, Computational Psychiatry, Antidepressant Dose Optimization, Major Depressive Disorder, Treatment Personalization, Clinical Decision Support Share and Cite: de ...
Geeky Gadgets

Ilya Sutskever Calls for Core AI Research : Scaling Won’t Take Us Further

What happens when the strategies that propelled an entire field to unprecedented heights begin to falter? For artificial intelligence, this is no longer a hypothetical question. After years of ...
Devdiscourse

Sophisticated AI promising but less reliable for monetary policy decisions

The study, titled Reinforcement Learning for Monetary Policy Under Macroeconomic Uncertainty: Analyzing Tabular and Function ...
Frontiers

Using reinforcement learning in genome assembly: in-depth analysis of a Q-learning assembler

Genome assembly remains an unsolved problem, and de novo strategies (i.e., those run without a reference) are relevant but computationally complex tasks in genomics. Although de novo assemblers have ...
The New York Times

‘Dept. Q’ Review: Netflix’s Nordic-British-American Noir

Matthew Goode plays a traumatized Edinburgh detective in a complicated cold-case series that’s less than the sum of its influences. By Mike Hale “Dept. Q,” this week’s new cop show on Netflix, is a ...
IEEE

Enhanced Reward Function Design for Source Term Estimation Based on Deep Reinforcement Learning

Abstract: This study investigates the design of reward functions for deep reinforcement learning-based source term estimation (STE). Estimating the properties of unknown hazardous gas leakage using a ...
Forbes

The Rise And Rise Of Reinforcement Learning: AI’s Quiet Revolution

Forbes contributors publish independent expert analyses and insights. Author, Researcher and Speaker on Technology and Business Innovation. Apr 19, 2025, 03:24am EDT Apr 21, 2025, 10:40am EDT ...
Scientific Research Publishing

Kumar, A., Zhou, A., Tucker, G. and Levine, S. (2020) Conservative Q-Learning for Offline Reinforcement Learning. Advances in Neural Information Processing Systems, 33, 1179-1191.

ABSTRACT: Offline reinforcement learning (RL) focuses on learning policies using static datasets without further exploration. With the introduction of distributional reinforcement learning into ...
Wired

Pioneers of Reinforcement Learning Win the Turing Award

In the 1980s, Andrew Barto and Rich Sutton were considered eccentric devotees to an elegant but ultimately doomed idea—having machines learn, as humans and animals do, from experience. Decades on, ...