Modern Engineering Marvels on MSN

AI inverse design boosts hydraulic pump efficiency by 32%

Can AI outperform decades of human expertise in mechanical design? Well, the researchers from Pusan National University gave ...
C&EN

Hybrid Frameworks Integrating Deep Learning and Optimization Methods for Inverse Design in Nanophotonics

Department of Electronics and Information Engineering, Korea University, Sejong 30019, Republic of Korea Division of Smart Energy Convergence Engineering, Korea University, 2511 Sejong-ro, Sejong ...
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

Inverse Q-Learning Optimal Control for Takagi–Sugeno Fuzzy Systems

Abstract: Inverse reinforcement learning optimal control is under the framework of learner–expert, the learner system can learn expert system's trajectory and optimal control policy via a ...
Seeking Alpha

Hedging Your Bets: Inverse Index ETFs Valuable Tools In Any Market

Inverse index ETFs like ProShares Short S&P 500 and ProShares Short Nasdaq-100 can effectively hedge portfolios during market downturns, enhancing long-term returns. Manual technical analysis and ...
eLife

Multiple Functions of Cerebello-Thalamic Neurons in Learning and Offline Consolidation of a Motor Skill in mice

This study provides evidence that cerebellar projections to the thalamus are required for learning and execution of motor skills in the accelerating rotarod task. This important study adds to a ...
marktechpost

Rethinking LLM Training: The Promise of Inverse Reinforcement Learning Techniques

Large language models (LLMs) have gained significant attention in the field of artificial intelligence, primarily due to their ability to imitate human knowledge through extensive datasets. The ...
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 ...
Frontiers

A reinforcement learning enhanced pseudo-inverse approach to self-collision avoidance of redundant robots

School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China Introduction: Redundant robots offer greater flexibility compared to non-redundant ones but are susceptible to ...