Ishita Dasgupta
Ishita Dasgupta
Research Scientist, DeepMind New York City
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Evaluating compositionality in sentence embeddings
I Dasgupta, D Guo, A Stuhlmüller, SJ Gershman, ND Goodman
arXiv preprint arXiv:1802.04302, 2018
Where do hypotheses come from?
I Dasgupta, E Schulz, SJ Gershman
Cognitive psychology 96, 1-25, 2017
Remembrance of inferences past: Amortization in human hypothesis generation
I Dasgupta, E Schulz, ND Goodman, SJ Gershman
Cognition 178, 67-81, 2018
Causal reasoning from meta-reinforcement learning
I Dasgupta, J Wang, S Chiappa, J Mitrovic, P Ortega, D Raposo, ...
arXiv preprint arXiv:1901.08162, 2019
A buried ionizable residue destabilizes the native state and the transition state in the folding of monellin
N Aghera, I Dasgupta, JB Udgaonkar
Biochemistry 51 (45), 9058-9066, 2012
A theory of learning to infer.
I Dasgupta, E Schulz, JB Tenenbaum, SJ Gershman
Psychological review 127 (3), 412, 2020
Resonating valence-bond physics on the honeycomb lattice
P Patil, I Dasgupta, K Damle
Physical Review B 90 (24), 245121, 2014
Memory as a computational resource
I Dasgupta, SJ Gershman
Trends in Cognitive Sciences, 2021
Learning to act by integrating mental simulations and physical experiments
I Dasgupta, KA Smith, E Schulz, JB Tenenbaum, SJ Gershman
bioRxiv, 321497, 2018
Analyzing Machine‐Learned Representations: A Natural Language Case Study
I Dasgupta, D Guo, SJ Gershman, ND Goodman
Cognitive Science 44 (12), e12925, 2020
Markov transitions between attractor states in a recurrent neural network
J Bernstein, I Dasgupta, D Rolnick, H Sompolinsky
2017 AAAI Spring Symposium Series, 2017
Amortized hypothesis generation
I Dasgupta, E Schulz, ND Goodman, SJ Gershman
BioRxiv, 137190, 2017
Are Convolutional Neural Networks or Transformers more like human vision?
S Tuli, I Dasgupta, E Grant, TL Griffiths
Proceedings of the Annual Meeting of the Cognitive Science Society 43 (43), 2021
Meta-Learning of Structured Task Distributions in Humans and Machines
S Kumar, I Dasgupta, JD Cohen, ND Daw, TL Griffiths
International Conference on Learning Representations, 2021, 2020
Heuristics, hacks, and habits: Boundedly optimal approaches to learning, reasoning and decision making.
I Dasgupta, E Schulz, JB Hamrick, J Tenenbaum
CogSci, 1-2, 2019
Passive attention in artificial neural networks predicts human visual selectivity
TA Langlois, HC Zhao, E Grant, I Dasgupta, TL Griffiths, N Jacoby
arXiv preprint arXiv:2107.07013, 2021
How does mental sorting scale?
S Haridi, C Wu, I Dasgupta, E Schulz
Proceedings of the Annual Meeting of the Cognitive Science Society 43 (43), 3413, 2021
Clustering and the efficient use of cognitive resources
I Dasgupta, TL Griffiths
PsyArXiv, 2021
Chunking as a rational solution to the speed-accuracy trade-off in a serial reaction time task
S Wu, N Éltetö, I Dasgupta, E Schulz
Algorithmic approaches to ecological rationality in humans and machines
I Dasgupta
Harvard University, 2019
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