Inductive biases for deep learning of higher-level cognition

A Goyal, Y Bengio - Proceedings of the Royal Society A, 2022 - royalsocietypublishing.org
A fascinating hypothesis is that human and animal intelligence could be explained by a few
principles (rather than an encyclopaedic list of heuristics). If that hypothesis was correct, we …

Next-generation deep learning based on simulators and synthetic data

CM de Melo, A Torralba, L Guibas, J DiCarlo… - Trends in cognitive …, 2022 - cell.com
Deep learning (DL) is being successfully applied across multiple domains, yet these models
learn in a most artificial way: they require large quantities of labeled data to grasp even …

Toward causal representation learning

B Schölkopf, F Locatello, S Bauer, NR Ke… - Proceedings of the …, 2021 - ieeexplore.ieee.org
The two fields of machine learning and graphical causality arose and are developed
separately. However, there is, now, cross-pollination and increasing interest in both fields to …

[图书][B] What babies know: Core Knowledge and Composition volume 1

E Spelke - 2022 - books.google.com
What do infants know? How does the knowledge that they begin with prepare them for
learning about the particular physical, cultural, and social world in which they live? Answers …

Threedworld: A platform for interactive multi-modal physical simulation

C Gan, J Schwartz, S Alter, D Mrowca… - arXiv preprint arXiv …, 2020 - arxiv.org
We introduce ThreeDWorld (TDW), a platform for interactive multi-modal physical simulation.
TDW enables simulation of high-fidelity sensory data and physical interactions between …

Clevrer: Collision events for video representation and reasoning

K Yi, C Gan, Y Li, P Kohli, J Wu, A Torralba… - arXiv preprint arXiv …, 2019 - arxiv.org
The ability to reason about temporal and causal events from videos lies at the core of human
intelligence. Most video reasoning benchmarks, however, focus on pattern recognition from …

Solver-in-the-loop: Learning from differentiable physics to interact with iterative pde-solvers

K Um, R Brand, YR Fei, P Holl… - Advances in Neural …, 2020 - proceedings.neurips.cc
Finding accurate solutions to partial differential equations (PDEs) is a crucial task in all
scientific and engineering disciplines. It has recently been shown that machine learning …

Resource-rational analysis: Understanding human cognition as the optimal use of limited computational resources

F Lieder, TL Griffiths - Behavioral and brain sciences, 2020 - cambridge.org
Modeling human cognition is challenging because there are infinitely many mechanisms
that can generate any given observation. Some researchers address this by constraining the …

[HTML][HTML] Neuroscience-inspired artificial intelligence

D Hassabis, D Kumaran, C Summerfield, M Botvinick - Neuron, 2017 - cell.com
The fields of neuroscience and artificial intelligence (AI) have a long and intertwined history.
In more recent times, however, communication and collaboration between the two fields has …

Graph networks as learnable physics engines for inference and control

A Sanchez-Gonzalez, N Heess… - International …, 2018 - proceedings.mlr.press
Understanding and interacting with everyday physical scenes requires rich knowledge
about the structure of the world, represented either implicitly in a value or policy function, or …