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A fascinating hypothesis is that human and animal intelligence could be explained by a few principles (rather than an encyclopedic list of heuristics).
Recurrent independent mechanisms, 2019a
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The theory of affordances
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An interactive activation model of context effects in letter perception: I. an account of basic findings
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Automatic/control processing and attention
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Intuitive physics
Michael McCloskey · 1983
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Automatic and conscious processing of social information
John A Bargh · 1984
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Distributed representations
Geoffrey E Hinton · 1984
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Object permanence in five-month-old infants
Renee Baillargeon, Elizabeth S Spelke, and Stanley Wasserman · 1985
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Conscious attention and abstraction in concept learning
Richard A Carlson and Don E Dulany · 1985
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From socrates to expert systems: The limits and dangers of calculative rationality
Hubert L Dreyfus · 1985
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The programmable blackboard model of reading
James L McClelland · 1986
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Sequential thought processes in pdp models
David E Rumelhart, Paul Smolensky, James L McClelland, and G Hinton · 1986
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James L McClelland, David E Rumelhart, PDP Research Group, et al · 1987
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Evolutionary principles in self-referential learning, or on learning how to learn: the meta-meta-… hook
Jürgen Schmidhuber · 1987
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Semantic networks
John F Sowa · 1987
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Connectionism and cognitive architecture: A critical analysis
Jerry A Fodor and Zenon W Pylyshyn · 1988
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On the proper treatment of connectionism
Paul Smolensky · 1988
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Learning a synaptic learning rule
Yoshua Bengio, Samy Bengio, and Jocelyn Cloutier · 1990
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Untersuchungen zu dynamischen neuronalen netzen [in german] diploma thesis
Sepp Hochreiter · 1991
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Direct transfer of learned information among neural networks
Lorien Y Pratt, Jack Mostow, Candace A Kamm, and Ace A Kamm · 1991
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Working memory
Alan Baddeley · 1992
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On the development of the reference prior method
James O Berger and José M Bernardo · 1992
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The reviewing of object files: Object-specific integration of information
Daniel Kahneman, Anne Treisman, and Brian J Gibbs · 1992
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Origins of knowledge
Elizabeth S Spelke, Karen Breinlinger, Janet Macomber, and Kristen Jacobson · 1992
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A cognitive theory of consciousness
Bernard J Baars · 1993
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Discriminability-based transfer between neural networks
Lorien Y Pratt · 1993
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Memory consolidation and the medial temporal lobe: a simple network model
Pablo Alvarez and Larry R Squire · 1994
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Learning long-term dependencies with gradient descent is difficult
Y Bengio, P Simard, and P Frasconi · 1994
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Training with noise is equivalent to tikhonov regularization
Chris M Bishop · 1995
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Neural networks for pattern recognition
Christopher M Bishop et al · 1995
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Markov chain Monte Carlo in practice
Walter R Gilks, Sylvia Richardson, and David Spiegelhalter · 1995
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Hierarchical recurrent neural networks for long-term dependencies
Salah Hihi and Yoshua Bengio · 1995
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Convolutional networks for images, speech, and time series
Yann LeCun, Yoshua Bengio, et al · 1995
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No free lunch theorems for search
David H Wolpert, William G Macready, et al · 1995
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Markov chain monte carlo convergence diagnostics: a comparative review
Mary Kathryn Cowles and Bradley P Carlin · 1996
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Bayesian model-building by pure thought: some principles and examples
Andrew Gelman · 1996
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Reasoning the fast and frugal way: models of bounded rationality
Gerd Gigerenzer and Daniel G Goldstein · 1996
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What’s in an object file? evidence from priming studies
Robert D Gordon and David E Irwin · 1996
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In the theatre of consciousness. global workspace theory, a rigorous scientific theory of consciousness
Bernard J Baars · 1997
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Multitask learning
Rich Caruana · 1997
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Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
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Parsing the stream of time: The value of event-based segmentation in a complex real-world control problem
Michael C Mozer and Debra Miller · 1997
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A neural global workspace model for conscious attention
James Newman, Bernard J Baars, and Sung-Bae Cho · 1997
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Rethinking eliminative connectionism
Gary F Marcus · 1998
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Child: A first step towards continual learning
Mark B Ring · 1998
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Collective dynamics of ‘small-world’networks
Duncan J Watts and Steven H Strogatz · 1998
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An embedded-processes model of working memory
Nelson Cowan · 1999
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A model of inductive bias learning
Jonathan Baxter · 2000
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Taking on the curse of dimensionality in joint distributions using neural networks
Samy Bengio and Yoshua Bengio · 2000
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Anterior cingulate and prefrontal cortex: who’s in control?
Jonathan D Cohen, Matthew Botvinick, and Cameron S Carter · 2000
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Causation, prediction, and search
Peter Spirtes, Clark N Glymour, Richard Scheines, and David Heckerman · 2000
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A neural probabilistic language model
Yoshua Bengio, Réjean Ducharme, and Pascal Vincent · 2001
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Very loopy belief propagation for unwrapping phase images
Brendan J Frey, Ralf Koetter, and Nemanja Petrovic · 2001
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Factor graphs and the sum-product algorithm
Frank R Kschischang, Brendan J Frey, and H-A Loeliger · 2001
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Efficient behavior of small-world networks
Vito Latora and Massimo Marchiori · 2001
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A rational analysis of cognitive control in a speeded discrimination task
Michael C Mozer, Michael Colagrosso, and David Huber · 2001
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Improved baselines with momentum contrastive learning
Xinlei Chen, Haoqi Fan, Ross Girshick, and Kaiming He · 2003
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Theories of access consciousness
Michael Colagrosso and Michael C Mozer · 2004
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The quest for consciousness a neurobiological approach
Christof Koch · 2004
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Learning the structure of markov logic networks
Stanley Kok and Pedro Domingos · 2005
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The persistence of object file representations
Nicholaus S Noles, Brian J Scholl, and Stephen R Mitroff · 2005
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Consciousness, emotion, and imagination
Murray Shanahan · 2005
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Applying global workspace theory to the frame problem
Murray Shanahan and Bernard Baars · 2005
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A fast learning algorithm for deep belief nets
Geoffrey E Hinton, Simon Osindero, and Yee-Whye Teh · 2006
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A cognitive architecture that combines internal simulation with a global workspace
Murray Shanahan · 2006
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Top-down versus bottom-up control of attention in the prefrontal and posterior parietal cortices
Timothy J Buschman and Earl K Miller · 2007
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Cortical mechanisms of action selection: the affordance competition hypothesis
Paul Cisek · 2007
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Using imagination to understand the neural basis of episodic memory
Demis Hassabis, Dharshan Kumaran, and Eleanor A Maguire · 2007
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The evolution of foresight: What is mental time travel, and is it unique to humans?
Thomas Suddendorf and Michael C Corballis · 2007
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Event perception: a mind-brain perspective
Jeffrey M Zacks, Nicole K Speer, Khena M Swallow, Todd S Braver, and Jeremy R Reynolds · 2007
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Top-down and bottom-up attention to memory: a hypothesis (atom) on the role of the posterior parietal cortex in memory retrieval
Elisa Ciaramelli, Cheryl L Grady, and Morris Moscovitch · 2008
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A unified architecture for natural language processing: Deep neural networks with multitask learning
Ronan Collobert and Jason Weston · 2008
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Top-down and bottom-up mechanisms in biasing competition in the human brain
Diane M Beck and Sabine Kastner · 2009
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Causality: Models, Reasoning, and Inference
Judea Pearl · 2009
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Do new caledonian crows solve physical problems through causal reasoning?
Alex H Taylor, Gavin R Hunt, Felipe S Medina, and Russell D Gray · 2009
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Why does unsupervised pre-training help deep learning?
Dumitru Erhan, Aaron Courville, Yoshua Bengio, and Pascal Vincent · 2010
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Goal-directed and habitual control in the basal ganglia: implications for parkinson’s disease
Peter Redgrave, Manuel Rodriguez, Yoland Smith, Maria C Rodriguez-Oroz, Stephane Lehericy, Hagai Bergman, Yves Agid, Mahlon R DeLong, and Jose A Obeso · 2010
Cited alongside, same era.
Artificial intelligence: A modern approach by stuart
Peter Norvig Russell · 2010
Cited alongside, same era.
Embodiment and the inner life: Cognition and Consciousness in the Space of Possible Minds
Murray Shanahan · 2010
Cited alongside, same era.
Conditional routing of information to the cortex: A model of the basal ganglia’s role in cognitive coordination
Andrea Stocco, Christian Lebiere, and John R Anderson · 2010
Cited alongside, same era.
Experimental and theoretical approaches to conscious processing
Stanislas Dehaene and Jean-Pierre Changeux · 2011
Cited alongside, same era.
Thinking, fast and slow
Mental labour
Wouter Kool and Matthew Botvinick · 2018
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Sequential attend, infer, repeat: Generative modelling of moving objects
Adam Kosiorek, Hyunjik Kim, Yee Whye Teh, and Ingmar Posner · 2018
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Generalization without systematicity: On the compositional skills of sequence-to-sequence recurrent networks
Brenden Lake and Marco Baroni · 2018
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Assessing generalization in deep reinforcement learning
Charles Packer, Katelyn Gao, Jernej Kos, Philipp Krähenbühl, Vladlen Koltun, and Dawn Song · 2018
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Efficient neural architecture search via parameter sharing
Hieu Pham, Melody Y Guan, Barret Zoph, Quoc V Le, and Jeff Dean · 2018
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alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Daniel Kahneman · 2011
Cited alongside, same era.
Learning a generative model of images by factoring appearance and shape
Nicolas Le Roux, Nicolas Heess, Jamie Shotton, and John Winn · 2011
Cited alongside, same era.
Interactions of top-down and bottom-up mechanisms in human visual cortex
Stephanie McMains and Sabine Kastner · 2011
Cited alongside, same era.
Frederick Eberhardt, Clark Glymour, and Richard Scheines · 2012
Cited alongside, same era.
Extending factor graphs so as to unify directed and undirected graphical models
Brendan J Frey · 2012
Cited alongside, same era.
Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
Cited alongside, same era.
On causal and anticausal learning
Bernhard Schölkopf, Dominik Janzing, Jonas Peters, Eleni Sgouritsa, Kun Zhang, and Joris Mooij · 2012
Cited alongside, same era.
Adam Santoro, Ryan Faulkner, David Raposo, Jack W. Rae, Mike Chrzanowski, Theophane Weber, Daan Wierstra, Oriol Vinyals, Razvan Pascanu, and Timothy P. Lillicrap · 2018
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Tensor field networks: Rotation-and translation-equivariant neural networks for 3d point clouds
Nathaniel Thomas, Tess Smidt, Steven Kearnes, Lusann Yang, Li Li, Kai Kohlhoff, and Patrick Riley · 2018
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Relational neural expectation maximization: Unsupervised discovery of objects and their interactions
Sjoerd Van Steenkiste, Michael Chang, Klaus Greff, and Jürgen Schmidhuber · 2018
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Rudder: Return decomposition for delayed rewards
Jose A Arjona-Medina, Michael Gillhofer, Michael Widrich, Thomas Unterthiner, Johannes Brandstetter, and Sepp Hochreiter · 2019
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Martin Arjovsky, Léon Bottou, Ishaan Gulrajani, and David Lopez-Paz · 2019
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Closure: Assessing systematic generalization of clevr models
Dzmitry Bahdanau, Harm de Vries, Timothy J O’Donnell, Shikhar Murty, Philippe Beaudoin, Yoshua Bengio, and Aaron Courville · 2019
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Emergent tool use from multi-agent autocurricula, 2019
Bowen Baker, Ingmar Kanitscheider, Todor Markov, Yi Wu, Glenn Powell, Bob McGrew, and Igor Mordatch · 2019
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A meta-transfer objective for learning to disentangle causal mechanisms
Yoshua Bengio, Tristan Deleu, Nasim Rahaman, Rosemary Ke, Sébastien Lachapelle, Olexa Bilaniuk, Anirudh Goyal, and Christopher Pal · 2019
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Learning representations using causal invariance
Leon Bottou · 2019
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Monet: Unsupervised scene decomposition and representation
Christopher P Burgess, Loic Matthey, Nicholas Watters, Rishabh Kabra, Irina Higgins, Matt Botvinick, and Alexander Lerchner · 2019
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Scaling data-driven robotics with reward sketching and batch reinforcement learning
Serkan Cabi, Sergio Gómez Colmenarejo, Alexander Novikov, Ksenia Konyushkova, Scott Reed, Rae Jeong, Konrad Zolna, Yusuf Aytar, David Budden, Mel Vecerik, et al · 2019
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Jeff Clune · 2019
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Causal reasoning from meta-reinforcement learning
Ishita Dasgupta, Jane Wang, Silvia Chiappa, Jovana Mitrovic, Pedro Ortega, David Raposo, Edward Hughes, Peter Battaglia, Matthew Botvinick, and Zeb Kurth-Nelson · 2019
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Genesis: Generative scene inference and sampling with object-centric latent representations
Martin Engelcke, Adam R Kosiorek, Oiwi Parker Jones, and Ingmar Posner · 2019
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Multi-object representation learning with iterative variational inference
Klaus Greff, Raphaël Lopez Kaufman, Rishabh Kabra, Nick Watters, Christopher Burgess, Daniel Zoran, Loic Matthey, Matthew Botvinick, and Alexander Lerchner · 2019
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Environmental drivers of systematicity and generalization in a situated agent
Felix Hill, Andrew Lampinen, Rosalia Schneider, Stephen Clark, Matthew Botvinick, James L McClelland, and Adam Santoro · 2019
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Learning neural causal models from unknown interventions
Nan Rosemary Ke, Olexa Bilaniuk, Anirudh Goyal, Stefan Bauer, Hugo Larochelle, Chris Pal, and Yoshua Bengio · 2019
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Joel Z Leibo, Edward Hughes, Marc Lanctot, and Thore Graepel · 2019
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Emergent coordination through competition
Siqi Liu, Guy Lever, Josh Merel, Saran Tunyasuvunakool, Nicolas Heess, and Thore Graepel · 2019
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Challenging common assumptions in the unsupervised learning of disentangled representations
Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Raetsch, Sylvain Gelly, Bernhard Schölkopf, and Olivier Bachem · 2019
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The algebraic mind: Integrating connectionism and cognitive science
Gary F Marcus · 2019
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Mastering atari, go, chess and shogi by planning with a learned model
Julian Schrittwieser, Ioannis Antonoglou, Thomas Hubert, Karen Simonyan, Laurent Sifre, Simon Schmitt, Arthur Guez, Edward Lockhart, Demis Hassabis, Thore Graepel, et al · 2019
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The bitter lesson
Richard Sutton · 2019
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Do we still need models or just more data and compute?
Max Welling · 2019
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Causalworld: A robotic manipulation benchmark for causal structure and transfer learning
Ossama Ahmed, Frederik Träuble, Anirudh Goyal, Alexander Neitz, Manuel Wüthrich, Yoshua Bengio, Bernhard Schölkopf, and Stefan Bauer · 2020
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Learning to recombine and resample data for compositional generalization
Ekin Akyürek, Afra Feyza Akyürek, and Jacob Andreas · 2020
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Language models are few-shot learners
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How We Learn: Why Brains Learn Better Than Any Machine… for Now
Stanislas Dehaene · 2020
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An image is worth 16x16 words: Transformers for image recognition at scale
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Unsupervised discovery of 3d physical objects from video
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An empirical investigation of the challenges of real-world reinforcement learning
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Addressing some limitations of transformers with feedback memory
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Generalizing convolutional neural networks for equivariance to lie groups on arbitrary continuous data
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Shortcut learning in deep neural networks
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Object files and schemata: Factorizing declarative and procedural knowledge in dynamical systems
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Amortized learning of neural causal representations
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Backpropagation and the brain
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An analysis of the adaptation speed of causal models
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Exploring the limits of transfer learning with a unified text-to-text transformer
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A benchmark for systematic generalization in grounded language understanding
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Unsupervised video decomposition using spatio-temporal iterative inference
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William Fedus, Barret Zoph, and Noam Shazeer · 2021
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The many faces of robustness: A critical analysis of out-of-distribution generalization
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Discrete-valued neural communication
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Multitask prompted training enables zero-shot task generalization
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E (n) equivariant graph neural networks
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Do as i can, not as i say: Grounding language in robotic affordances
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Using cognitive psychology to understand gpt-3
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Typing assumptions improve identification in causal discovery
Philippe Brouillard, Perouz Taslakian, Alexandre Lacoste, Sébastien Lachapelle, and Alexandre Drouin · 2022
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Palm: Scaling language modeling with pathways
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Bayesian structure learning with generative flow networks
Tristan Deleu, António Góis, Chris Chinenye Emezue, Mansi Rankawat, Simon Lacoste-Julien, Stefan Bauer, and Yoshua Bengio · 2022
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Priors in bayesian deep learning: A review
Vincent Fortuin · 2022
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Retrieval-augmented reinforcement learning
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Bc-z: Zero-shot task generalization with robotic imitation learning
Eric Jang, Alex Irpan, Mohi Khansari, Daniel Kappler, Frederik Ebert, Corey Lynch, Sergey Levine, and Chelsea Finn · 2022
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Towards understanding how machines can learn causal overhypotheses
Eliza Kosoy, David M Chan, Adrian Liu, Jasmine Collins, Bryanna Kaufmann, Sandy Han Huang, Jessica B Hamrick, John Canny, Nan Rosemary Ke, and Alison Gopnik · 2022
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Unified-io: A unified model for vision, language, and multi-modal tasks
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Inventing relational state and action abstractions for effective and efficient bilevel planning
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