GitHub

mll-lab-nu/VAGEN

Kangrui Wang*, Pingyue Zhang*, Zihan Wang*, Yaning Gao*, Linjie Li*, Qineng Wang, Hanyang Chen, Chi Wan, Yiping Lu, Zhengyuan Yang, Lijuan Wang, Ranjay Krishna, Jiajun Wu, Li Fei-Fei, Yejin Choi, ...
University News & Events

Brain organoids can be trained to solve a goal-directed task

UC Santa Cruz researchers are exploring how brains learn, adapt, and improve, which could help us better understand and address neurological conditions.
IEEE

Adaptive Neural Network Algorithm with Reinforcement Learning

Abstract: Neural network algorithm (NNA) is a new type of population-based meta-heuristic algorithm, which is inspired by artificial neural networks. NNA is a result of the deep integration of ...
GitHub

[ICRA 2026] KINESIS: Reinforcement Learning-Based Motion Imitation for Physiologically Plausible Musculoskeletal Motor Control

KINESIS is a model-free imitation-learning framework that facilitates the development of effective and scalable muscle-based control policies of locomotion. KINESIS is trained on 1.8 hours of ...
IEEE

Audio-Driven Reinforcement Learning for Head-Orientation in Naturalistic Environments

Abstract: Although deep reinforcement learning (DRL) approaches in audio signal processing have seen substantial progress in recent years, fully audio-driven DRL for tasks such as navigation, gaze ...