![]() Learning Data Representation: Hierarchies and Invariance.Engineering and Reverse Engineering Reinforcement Learning.Neural Information Processing Systems (NIPS) 2015.Biophysical principles of brain oscillations and their meaning for information processing.Deep Learning: Theory, Algorithms and Applications.CBMM Workshop on Speech Representation, Perception and Recognition.Science of Intelligence: Computational Principles of Natural and Artificial Intelligence.A workshop on language and vision at CVPR 2017.Learning Disentangled Representations: from Perception to Control.A workshop on language and vision at CVPR 2018.A workshop on language and vision at CVPR 2019.Shared Visual Representations in Human and Machine Intelligence (SVRHM) Workshop 2019.MLCC 2020 simula Machine Learning Crash Course.REGML 2020 | Regularization Methods for Machine Learning.Shared Visual Representations in Human & Machine Intelligence (SVRHM) 2020.Shared Visual Representations in Human & Machine Intelligence (SVRHM) 2021.Shared Visual Representations in Human & Machine Intelligence (SVRHM) 2022.Information-Theoretic Principles in Cognitive Systems.Undergraduate Summer Research Internships in Neuroscience.Theoretical Frameworks for Intelligence.Neurally-plausible mental-state recognition from observable actions.Sleep Network Dynamics Underlying Flexible Memory Consolidation and Learning.Invariance in Visual Cortex Neurons as Defined Through Deep Generative Networks.Computational models of human social interaction perception. ![]() Modeling Human Goal Inference as Inverse Planning in Real Scenes.Memory and Executive Function | Brain OS. ![]()
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