Jun Izawa
@IzawaLabTsukubaAssociate Professor, University of Tsukuba
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Our paper 'Meta-learning of human motor adaptation via the dorsal premotor cortex' is now published in PNAS. We examine the role of the dorsal premotor cortex in meta-learning of motor adaptation using TMS: pnas.org/doi/abs/10.107… #Motorlearning
Does your ethics review board or IRB or Human Research Committee require sample size justification for non-clinical trials? Should it?
Meta-Learning of Motor Skills in the Dorsal Premotor Cortex of the Brain | Research News - University of Tsukuba tsukuba.ac.jp/en/research-ne…
Our latest paper investigates the impact of meta-learning ability on rehabilitation outcomes following a stroke. The study explores how 'learning-to-learn,' a crucial metacognitive skill for motor learning, correlates with functional recovery. minervamedica.it/en/journals/eu…
(mini-symposium) QB3:Qualia, Brain, Body, Behavior 15 Jan at ATR atr.jp/map_etc/access… Register is open till Jan 9 forms.gle/JkypL1cEAiatzP… Speakers: Mizuki Oka (U Tsukuba), Tatsuya Daikoku (U Tokyo), Jun Izawa (U Tsukuba), Nao Tsuchiya (ATR/Monash), Aurelio Cortese (ATR)
Pleased to announce that I have assumed the role of Action Editor for Neural Networks! Anticipating contributions to the field of computational motor control. sciencedirect.com/journal/neural…
Collection of metacognition nature.com/collections/fj…
Metalearning Machines Learn to Learn (1987-) One of my favorite paper, for a record this paper 26 years old. By @SchmidhuberAI people.idsia.ch/~juergen/metal…
Preserved metacognition for undetected visuomotor deviations jneurosci.org/content/early/…
Meta-learning discovers language skills. arxiv.org/abs/2306.08400
The essential step there will be the constitution of a model (or in weaker instances, a simulation) of the phenomenon (Figure 2).
Super piece on critical thinking by one of the most original leaders in microbiology: ami-journals.onlinelibrary.wiley.com/doi/full/10.11…
Motor learning experiment at home: physoc.onlinelibrary.wiley.com/share/SCVH6M95…
Meta-learning is a hot topic in AI, but how does it look in nature? I wrote a short review for Current Opinion in Behavioral Sciences that tries explores this question, hope you enjoy! Meta-learning in natural and artificial intelligence: authors.elsevier.com/a/1cTXd8MqMif3…
new pre-print: "Reverse engineering the self" (by L.A. Paul, me, Julian De Freitas @JulianDeFreitas, and Josh Tenenbaum) In which we combine philosophy, cog-sci & CS to propose a framework for reverse-engineering an agent that can “think for itself” psyarxiv.com/vzwrn/
1/5) I am happy to share our latest work on the integration of the neuroscience of memory and (meta-) reinforcement learning, in collaboration with @FOlafsdottir Rethinking the hippocampal cognitive map as a meta-learning computational module cell.com/trends/cogniti…
Linear Representation Meta-Reinforcement Learning for Instant Adaptation. arxiv.org/abs/2101.04750
Meta-reinforcement learning quickly adapts to new tasks by learning strong inductive biases. This is done via a slower outer learning loop training on a distribution of tasks, leading to an inner loop that rapidly adapts by maintaining a history of past actions and observations.
A key challenge in #ReinforcementLearning is learning policies from scratch in environments with complex tasks. Read how a meta-algorithm, Jump Start Reinforcement Learning, uses prior policies to create a learning curriculum that improves performance → goo.gle/38zqllB
Let me introduce two fun papers from one of my side projects. (1) Meta Reinforcement Learning for Optimal Design of Legged Robots arxiv.org/abs/2210.02750 (2) Learning-based Design and Control for Quadrupedal Robots with Parallel-Elastic Actuators: arxiv.org/abs/2301.03509
Meta-reinforcement learning in a thalamo-orbitofrontal circuit biorxiv.org/content/10.110…
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