01/

Konrad Kording

• Experimental psychologists concerns regarding localization of brain function 

• Epistemic issues about decomposition of function

• Focused critique of neuroscience methods

• Ability of standard methods to decode even a "neuro" algorithm

• Grow neurons outside of the brain and study their independent behaviour

• Computing by time

02/

Adrienne Fairhall

• None listed

03/

Melanie Mitchell

• An Evolutionary Perspective on Biological and ANNs

• On the Measure of Intelligence

• Relationships in Analogical Reasoning

• Do Better ImageNet Models Transfer Better?

• Continual Learning

04/

Anthony Zador

• More is Different

05/

Marcin Miłkowski

• Short overview of Fodor's ideas

• Modularity of Mind

• Affordances in contemporary reinforcement learning

• Why normative models in neuroscience

• Integrated Information Theory

• Super Turing Machines 1

• Super Turing Machines 2

• Origin of Common Sense

• Anomalous Monism

• Neuromorphic Computing

• Building Machines That Learn And Think Like People

• Pancomputationalism

• Meta Meta

• Extended spider cognition

• Environment's role in cognition

• Locating the engram

• Homeostatic reinforcement learning

• Collective Memories 1

• Collective Memories 2

06/

Paul Cisek

• Materialism Eliminative

• Principles of Brain Evolution

• Evolutionary Neuroscience

• A Theory of Affordances in Reinforcement Learning

• Précis of principles of brain evolution

• A Modular Approach to Vocal Learning

• The Theory of Affordances

• The emergence of grammar

• Homeostatic reinforcement learning

• Paul Cisek about the semantic mess of "representations"

• Animal Cultures

07/

Recap and Panel Discussion

• Complexity & Stupidity

• What is Computation?

• No one knows what attention is

08/

John Langford

• Of exactitude in science

• Somatic_hypermutation

• Placing language in an integrated understanding system

• Humpback whale song hierarchical structure

• Syntactic features in humpback whale song

09/

Blake Richards

• Hippocampal Contributions to Control

• Optimizing agent behavior over long time scales by transporting value

• Marc Howard

• Hidden neural states underlie canary song syntax

• The Mind of a Mnemonist

• Complementary learning systems within the hippocampus

• Consistent Nonparametric Regression

• On the Strong Universal Consistency of Nearest Neighbor Regression

• The primacy of behavioral research for understanding the brain

• Tensor Product Variable Binding and the Representation of Symbolic Structures in Connectionist Systems

• On the proper treatment of connectionism

• Sparse Distributed Models

• What Constitutes an Episode in Episodic Memory?

• Reward prediction errors create event boundaries in memory

• A Scale-Invariant Internal Representation of Time

• Learning Structures: Predictive Representations, Replay, and Generalization

• Inhibitory engrams in perception and memory

• Janice Chen

10/

Jay McClelland

• Environmental drivers of systematicity and generalization in a situated agent

• Placing language in an integrated understanding system

• Aetherial Symbols

• Prefrontal cortex as a meta-reinforcement learning system

• Cultural diversity in chimpanzees

• Formal Statement

• Are Neural Nets Modular?

• Compositional Deep Learning

• Measuring Compositionality in Representation Learning

• Factorizing Declarative and Procedural Knowledge in Dynamical Systems

• Learning Basic Visual Concepts with a Constrained Variational Framework

• The Scattering Compositional Learner

11/

Gary Marcus

• Honey bees can perform delay-match-to-sample

• Compositional Reasoning in Early Childhood

• Addition and subtraction by human infants

• A unified account of numerosity perception

• Optogenetic Editing Reveals the Hierarchical Organization of Learned Action Sequences

• Hand Knob Area of Premotor Cortex Represents the Whole Body in a Compositional Way

• Journal of compositionality

• DNN or k-NN

• A brief survey of classic work on compositionality

• Compositionality

• Formal Semantics Pragmatics: Origins, Issues, Impact

• Compositionality as an Empirical Problem

• Performance vs. competence in human–machine comparisons

• Mental Structures

• Object Files and Schemata: Factorizing Declarative and Procedural Knowledge in Dynamical Systems

• Learning Physical Graph Representations from Visual Scenes

• On Meaning, Form, and Understanding in the Age of Data

• Object Representations for Learning and Reasoning

• The inverted T-model

• Entity Abstraction in Visual Model-Based Reinforcement Learning

• Improving Generative Imagination in Object-Centric World Models

• Compositionality as an empirical problem

12/

Jessica Hamrick

• Structured agents for physical construction

• The Spatial Memory Pipeline

• Generalization as Search

• When to use parametric models in reinforcement learning?

• Model-based RL in Contextual Decision Processes

• State, Transition and Learning Interactions in the Two-Step Task

• Predictive representations can link modelbased reinforcement learning to model-free mechanisms

• Is a Good Representation Sufficient for Sample Efficient Reinforcement Learning?

• Cerebellar Involvement in Anticipating the Consequences of Self-Produced Actions During Bimanual Movements

• Acme: a research framework for reinforcement learning

• Monte-Carlo Tree Search (MCTS)

• Tutorial on Model-Based Methods in Reinforcement Learning

• The successor representation in human reinforcement learning

• Human-level concept learning through probabilistic program induction

• ALFWorld: Aligning Text and Embodied Environments for Interactive Learning

• Planning to Explore via Self-Supervised World Models

• Investigating Human Priors for Playing Video Games

• Blueberry Earth

• On the role of planning in model-based deep reinforcement learning

• A normative account of confirmatory biases during reinforcement learning

13/

Mazviita Chirimuuta

• Outside Color

• The Algorithmic Lens

• Is coding a relevant metaphor for the brain?

• Do you compute?

• The Church-Turing Thesis

• The Halting Problem

• Representation of Events in Nerve Nets and Finite Automata

14/

Iris van Rooij

• Why Philosophers Should Care About Computational Complexity

• Levels of biological plausibility

• Satisficing

• Similar network activity from disparate circuit parameters

• Every Model Learned by Gradient Descent Is Approximately a Kernel Machine

• Monoids, weighted automata and algorithmic philosophy of science

• Against Method

15/

Recap and Panel Discussion

• Virtual Neuroscience with The Learning Salon

• Can a bird brain do phonology?

• Baffling: a condition-dependent alternative mate attraction strategy using self-made tools in tree crickets

• Tree crickets optimize the acoustics of baffles to exaggerate their mate-attraction signal

• The Model-less Neuromimetic Chip and its Normalization of Neuroscience and Artificial Intelligence

• The Foundations of Computing

• The maps problem and the mapping problem: Two challenges for a cognitive neuroscience of speech and language

• Probably Approximately Correct: Nature's Algorithms for Learning and Prospering in a Complex World

• The Contribution of Area MT to Visual Motion Perception Depends on Training

• Acute off-target effects of neural circuit manipulations

• Reverse hierarchies and sensory learning

• Object Files and Schemata: Factorizing Declarative and Procedural Knowledge in Dynamical Systems

• ON THE RELATIONSHIP OF ACTIVE INFERENCE AND CONTROL AS INFERENCE

• On the Origin of Objects

• And the New Yorker Cartoon Contest Winner Is … a Computer

• Causal Inference Book

• Intrinsic Social Motivation via Causal Influence in Multi-Agent RL

• The Animal-AI Testbed

• Scaling Laws for Neural Language Models

• Memory and the Computational Brain