15 papers
Meta-Representational Predictive Coding: Neuroscience-Informed Self-Supervised Learning
Alexander Ororbia, Karl Friston, Rajesh P. N. Rao
Self-supervised learning has become an increasingly important paradigm in the domain of machine intelligence. Furthermore, evidence for self-supervised adaptation, such as contrast…
Error Highways: Scaling Predictive Coding to Very Deep Networks
Amirhossein Mohammadi, Alexander G. Ororbia
Predictive coding networks (PCNs) offer a biologically-plausible, local-learning alternative to back-propagation of errors (backprop). Nevertheless, they have remained largely conf…
Intrinsic Vicarious Conditioning for Deep Reinforcement Learning
Rodney A Sanchez, Ferat Sahin, Alex Ororbia +1
Advancements in reinforcement learning have produced a variety of complex and useful intrinsic driving forces; crucially, these drivers operate under a direct conditioning paradigm…
NeuroAI and Beyond: Bridging Between Advances in Neuroscience and ArtificialIntelligence
Anthony Zador, Jean-Marc Fellous, Terrence Sejnowski +28
Neuroscience and Artificial Intelligence (AI) have made impressive progress in recent years but remain only loosely interconnected. Based on a workshop convened by the National Sci…
Optimizing Neurorobot Policy under Limited Demonstration Data through Preference Regret
Viet Dung Nguyen, Yuhang Song, Anh Nguyen +3
Robot reinforcement learning from demonstrations (RLfD) assumes that expert data is abundant; this is usually unrealistic in the real world given data scarcity as well as high coll…
Enhancing Eye Feature Estimation from Event Data Streams through Adaptive Inference State Space Modeling
Viet Dung Nguyen, Mobina Ghorbaninejad, Chengyi Ma +5
Eye feature extraction from event-based data streams can be performed efficiently and with low energy consumption, offering great utility to real-world eye tracking pipelines. Howe…