Ishita Dasgupta

发表

Meta-Learning of Structured Task Distributions in Humans and Machines

Thomas L. Griffiths, Jonathan D. Cohen, Nathaniel D. Daw, 2020, ICLR.

Markov Transitions between Attractor States in a Recurrent Neural Network

David Rolnick, Haim Sompolinsky, Jeremy Bernstein, 2017, AAAI Spring Symposia.

Where do hypotheses come from?

S. Gershman, Ishita Dasgupta, Eric Schulz, 2017, Cognitive Psychology.

Causal Reasoning from Meta-reinforcement Learning pdf

Zeb Kurth-Nelson, Silvia Chiappa, Matthew Botvinick, 2019, ArXiv.

A theory of learning to infer.

Eric Schulz, Joshua B Tenenbaum, Ishita Dasgupta, 2020, Psychological review.

Remembrance of inferences past: Amortization in human hypothesis generation

Noah D. Goodman, S. Gershman, Ishita Dasgupta, 2018, Cognition.

LEARNING STRUCTURE FROM THE GROUND UP: HIERARCHICAL REPRESENTATION LEARNING BY CHUNKING

Ishita Dasgupta, 2021 .

Running head : LEARNING TO INFER 1 A theory of learning to infer

S. Gershman, Ishita Dasgupta, Eric Schulz, 2019 .

Meta-reinforcement learning of causal strategies

Pedro A. Ortega, Jane X. Wang, M. Botvinick, 2019 .

CBMM Memo No . 056 October 24 , 2016 Where do hypotheses come from ?

S. Gershman, Ishita Dasgupta, Eric Schulz, 2022 .

Tell me why! - Explanations support learning of relational and causal structure pdf

Andrew K. Lampinen, James L. McClelland, Felix Hill, 2021, ArXiv.

Tell me why! Explanations support learning relational and causal structure

James L. McClelland, Andrew Kyle Lampinen, Nicholas A. Roy, 2021, ICML.

Algorithmic approaches to ecological rationality in humans and machines

Ishita Dasgupta, Ishita Dasgupta, I. Dasgupta, 2020 .

A theory of learning to infer

Samuel J. Gershman, Joshua B. Tenenbaum, Eric Schulz, 2019, bioRxiv.

Memory as a Computational Resource

S. Gershman, Ishita Dasgupta, I. Dasgupta, 2021, Trends in Cognitive Sciences.

Using Natural Language and Program Abstractions to Instill Human Inductive Biases in Machines

Robert D. Hawkins, Carlos G. Correa, T. Griffiths, 2022, NeurIPS.

Disentangling Abstraction from Statistical Pattern Matching in Human and Machine Learning

T. Griffiths, N. Daw, Sreejan Kumar, 2022, PLoS Comput. Biol..

Passive attention in artificial neural networks predicts human visual selectivity pdf

Thomas L. Griffiths, Erin Grant, Nori Jacoby, 2021, NeurIPS.

Collaborating with language models for embodied reasoning

R. Fergus, Arun Ahuja, Felix Hill, 2023, ArXiv.

Distilling Internet-Scale Vision-Language Models into Embodied Agents

R. Fergus, Arun Ahuja, Ishita Dasgupta, 2023, ICML.

Are Convolutional Neural Networks or Transformers more like human vision? pdf

Thomas L. Griffiths, Erin Grant, Ishita Dasgupta, 2021, ArXiv.

Transformers generalize differently from information stored in context vs in weights

Andrew Kyle Lampinen, Stephanie C. Y. Chan, D. Kumaran, 2022, ArXiv.

Can language models learn from explanations in context?

James L. McClelland, Andrew Kyle Lampinen, Michael Henry Tessler, 2022, EMNLP.

Learning to Navigate Wikipedia by Taking Random Walks

R. Fergus, Will Grathwohl, Arun Ahuja, 2022, NeurIPS.

Learning Structure from the Ground up - Hierarchical Representation Learning by Chunking

Ishita Dasgupta, Eric Schulz, N. Éltető, 2022, NeurIPS.

Remembrance of inferences past: Amortization in human hypothesis generation

Noah D. Goodman, S. Gershman, Ishita Dasgupta, 2018, Cognition.

The scaling of mental computation in a sorting task

Charley M. Wu, Ishita Dasgupta, Eric Schulz, 2023, Cognition.

Language models show human-like content effects on reasoning

James L. McClelland, Andrew Kyle Lampinen, Stephanie C. Y. Chan, 2022, ArXiv.

Journal of Mathematical Psychology

Ishita Dasgupta, Thomas L. Griffiths, 2022 .

Meta-Learned Models of Cognition

Jane X. Wang, M. Botvinick, Ishita Dasgupta, 2023, The Behavioral and brain sciences.

Are Convolutional Neural Networks or Transformers more like human vision?

T. Griffiths, Erin Grant, Ishita Dasgupta, 2021, CogSci.

Passive learning of active causal strategies in agents and language models

Andrew Kyle Lampinen, Stephanie C. Y. Chan, Jane X. Wang, 2023, NeurIPS.

AI Crop Predictor and Weed Detector Using Wireless Technologies: A Smart Application for Farmers

Ishita Dasgupta, Jayit Saha, Pattabiraman Venkatasubbu, 2020, Arabian Journal for Science and Engineering.

Distinguishing rule- and exemplar-based generalization in learning systems

T. Griffiths, Erin Grant, Ishita Dasgupta, 2021, ICML.

Machine Psychology

Andrew Kyle Lampinen, Thilo Hagendorff, Ishita Dasgupta, 2023, 2303.13988.