A Less Artificial Intelligence - Neuroscience and AI Co-evolution
Explore the intersection of neuroscience and AI through Andreas Tolias's examination of developing more natural and brain-inspired artificial intelligence systems at Stanford's symposium.
Basic Kinematics of Mice Reinforcement Learning in Intelligent Cages
Explore reinforcement learning in mice using intelligent cages, combining point processes and behavioral analysis to study learning and social aspects in experimental settings.
Complex Networks and Applications to Neuroscience - Class 3
Explore complex networks' applications in neuroscience, focusing on advanced concepts and their relevance to brain function and connectivity.
Collective Behaviors in Neuronal Networks Under the Actions of Electric and Magnetic Fields
Explore collective behaviors in neuronal networks influenced by electric and magnetic fields, examining dynamics and implications for complex network processes.
Mapping Brain Dynamics and Trajectories with Geometric and Topological Machine Learning
Explore geometric and topological machine learning techniques for mapping brain dynamics and trajectories, enhancing understanding of neural processes.
Bridging Associative Memory and Probabilistic Modeling
Explore the connection between associative memory and probabilistic modeling in this insightful presentation by Rylan Schaeffer.
Learning Probability Distributions of Neuronal Activity Patterns - Max Entropy Models
Explore max entropy models for understanding neuronal activity patterns and probability distributions in biological systems.
Mapping Artificial and Natural Intelligence
Explore the intersection of artificial and natural intelligence with Gabriel Aeppli, delving into quantum materials, inhomogeneities, frustration, and topology.
Nonlinear Dynamics of Neuronal Models with Applications to Bird Song Dynamics - Class 3
Explore nonlinear dynamics in neuronal models and their application to bird song, focusing on advanced concepts and real-world implications in neuroscience.
Towards Biologically Plausible Intelligence
Explore biologically plausible intelligence with Dr. Christos Papadimitriou's seminar, delving into cutting-edge research on brain-inspired computational models and cognitive processes.
Класифікація стимулів в реверберативній імпульсній нейронній мережі
Дослідіть класифікацію стимулів у реверберативних імпульсних нейронних мережах через призму теоретичної фізики та нейронауки під керівництвом провідного науковця.
Основи роботи нейромереж
Дізнайтеся про фундаментальні принципи та механізми функціонування нейронних мереж, їх архітектуру та практичне застосування в сучасних технологіях.
Computational Principles Underlying the Learning of Sensorimotor Repertoires
Explore the computational principles behind human motor learning and memory formation, focusing on contextual inference's role in developing movement skills and behavioral adaptations.
Organizing Knowledge for Flexible Behavior in Neural Networks
Explore groundbreaking research on how the brain organizes and generalizes knowledge, focusing on hippocampal models, neural populations, and grid cells in flexible behavior and intelligence.
Molecular Neuromorphic Building Blocks for Artificial Intelligence
Explore cutting-edge molecular neuromorphic computing and its applications in AI through groundbreaking research on building blocks that mimic neural processes and brain-like functionality.
Modeling Bottom-Up and Top-Down Visual Attention in Humans and Monkeys - 2009
Explore computational models of visual attention combining bottom-up and top-down influences, comparing predictions to human and monkey behavior, with applications to real-world vision challenges.
Emergent Computation and Learning from Assemblies of Neurons
Explore emergent computation and learning in neural assemblies with Dr. Santosh Vempala's insightful seminar on cutting-edge neuroscience research.
Leveraging the Allen Brain Observatories
Explore neural dynamics through Allen Brain Observatories, gaining insights into brain function and advanced neuroscience research techniques.
Reinforcement Learning and Architectures of Intelligence - Part 3
Explore advanced reinforcement learning concepts and intelligence architectures with Microsoft Research's Ida Momennejad in this in-depth tutorial from IPAM's Mathematics of Intelligences series.
Normalization Models of Attention - From Neural Computation to Behavioral Goals
Explore how attention interacts with neural normalization to shape perception and behavior, featuring hands-on MATLAB exercises and computational modeling frameworks for cognitive processing.
Neural Machines: From Fruit Flies to Embedded Devices
Explore neural machines through biological and artificial systems, from fruit fly olfactory architectures to low-power embedded devices, revealing innovative approaches to lifelong learning and adaptation.