BEGIN:VCALENDAR
VERSION:2.0
PRODID:-// - ECPv6.15.16//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-ORIGINAL-URL:https://www.neuropac.info
X-WR-CALDESC:Events for 
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/New_York
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20240310T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20241103T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20250309T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20251102T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20260308T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20261101T060000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;VALUE=DATE:20250714
DTEND;VALUE=DATE:20250726
DTSTAMP:20260417T083403
CREATED:20250529T111246Z
LAST-MODIFIED:20250529T111246Z
UID:10000338-1752451200-1753487999@www.neuropac.info
SUMMARY:NeuroAI Live Online Course by Neuromatch
DESCRIPTION:Full time\, 2 Week\, Live Instruction Course \nWhat are common principles of natural and artificial intelligence? \nThe core challenge of intelligence is generalization. Neuroscience\, cognitive science\, and AI are all questing for principles that help generalization. Major system features that affect generalization include: task structure (multitasking\, multiple inputs with same output and vice versa)\, microcircuitry (nonlinearities\, canonical motifs and their operations\, sparsity)\, macrocircuitry or architecture (e.g. modules for memory\, information segregation\, weight sharing by input symmetry or common development)\, learning rules (synaptic plasticity\, modulation)\, and data stream (e.g. curriculum). \nWe aim to present current understanding of how these issues arise in both natural and artificial intelligence\, comparing how these system features affect representations\, computations\, and learning. We provide case studies and coding exercises that illustrate these issues in neuroscience\, cognitive science and AI. \n\nLearning Goal 1: A common understanding and vocabulary to describe challenges faced by naturally intelligent systems\n\nDescribe core shared concepts in neuroscience\, cognitive science and machine learning and how they differ to each other\nDescribe and implement different ways in which an ANN can be compared to a BNN\nDescribe multiple scales of computation\, and multiple scales of study (e.g. Marr’s levels\, what/how/why?)\n\n\nLearning Goal 2: Experience a multiplicity of approaches and interests at the intersection of neuro and AI; be able to describe some of these approaches and interests\nLearning Goal 3: Be able to practically implement NeuroAI models\n\nCoding and training models\nAdding more features to existing models\nDebugging (within guardrails)\nInterpreting\, analyzing and critiquing existing models\n\n\nLearning Goal 4: Complete research that deals with difficulties in NeuroAI\n\nWriting down a problem in a way that makes it tractable\nInteracting with other people from other disciplines fruitfully\nDo research (reading papers\, implementing previous SOTA\, coding new methods\, evaluating diff methods) in NeuroAI\nCommunicating their research in ways that are comprehensible to their target audience\n\n\n\nAll our content is open source\, you can see the NeuroAI course book here.
URL:https://www.neuropac.info/event/neuroai-live-online-course-by-neuromatch/
LOCATION:Online
CATEGORIES:School
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20250714
DTEND;VALUE=DATE:20250802
DTSTAMP:20260417T083403
CREATED:20250205T093745Z
LAST-MODIFIED:20250205T093745Z
UID:10000324-1752451200-1754092799@www.neuropac.info
SUMMARY:NeuroAI – Neuroscience and AI Summer School
DESCRIPTION:Modern deep learning methods provide some of the best tools to model behavior and brain function today. Excitingly\, AI systems have become the first artificial models capable of matching human performance in sophisticated cognitive tasks\, such as visual recognition\, language processing\, and strategic planning. This unique capability makes them a key test bed for neuroscience research: by studying how these AI systems solve complex problems\, we can generate and test hypotheses about the computational principles that biological brains might use. Moreover\, thanks to amazing progress in neuroscientific experimental recording techniques over the last decade\, we now have access to vast amounts of complex data\, which can be used in computational modeling\, across multiple modalities – from neural activity of thousands of neurons\, to anatomical details of neuronal circuits\, to whole brain neural recordings during complex behavior of humans and animals. These exciting developments—in both AI methodology and neuroscientific recordings—have inspired an emerging area of research at the intersection of neuroscience and AI. \n  \nThe course gives a hands-on introduction to modern AI methods\, including deep learning\, and how it can be used for analyzing and modeling brain activity and behavior. Experts in the field will teach the basics of AI\, and how to use them as models of the brain\, cognition\, and behavior. \n\n 
URL:https://www.neuropac.info/event/neuroai-neuroscience-and-ai-summer-school/
LOCATION:Champalimaud Centre for the Unknown\, Portugal\, Lisbon\, Portugal
CATEGORIES:School
END:VEVENT
END:VCALENDAR