Zobrazeno 1 - 10
of 2 361
pro vyhledávání: '"Grigsby P"'
Language models trained on diverse datasets unlock generalization by in-context learning. Reinforcement Learning (RL) policies can achieve a similar effect by meta-learning within the memory of a sequence model. However, meta-RL research primarily fo
Externí odkaz:
http://arxiv.org/abs/2411.11188
Autor:
Grigsby, J. Elisenda, Lindsey, Kathryn
For any fixed feedforward ReLU neural network architecture, it is well-known that many different parameter settings can determine the same function. It is less well-known that the degree of this redundancy is inhomogeneous across parameter space. In
Externí odkaz:
http://arxiv.org/abs/2410.17191
Autor:
Jenniskens, Peter, Estrada, Paul R., Pilorz, Stuart, Gural, Peter S., Samuels, Dave, Rau, Steve, Abbott, Timothy M. C., Albers, Jim, Austin, Scott, Avner, Dan, Baggaley, Jack W., Beck, Tim, Blomquist, Solvay, Boyukata, Mustafa, Breukers, Martin, Cooney, Walt, Cooper, Tim, De Cicco, Marcelo, Devillepoix, Hadrien, Egland, Eric, Fahl, Elize, Gialluca, Megan, Grigsby, Bryant, Hanke, Toni, Harris, Barbara, Heathcote, Steve, Hemmelgarn, Samantha, Howell, Andy, Jehin, Emmanuel, Johannink, Carl, Juneau, Luke, Kisvarsanyi, Erika, Mey, Philip, Moskovitz, Nick, Odeh, Mohammad, Rachford, Brian, Rollinson, David, Scott, James M., Towner, Martin C., Unsalan, Ozan, van Wyk, Rynault, Wood, Jeff, Wray, James D., Pavao, C., Lauretta, Dante S.
Publikováno v:
Icarus, 2024
In the late stages of accretion leading up to the formation of planetesimals, particles grew to pebbles the size of 1-mm to tens of cm. That is the same size range that dominates the present-day comet mass loss. Meteoroids that size cause visible met
Externí odkaz:
http://arxiv.org/abs/2408.11945
The challenge of visual grounding and masking in multimodal machine translation (MMT) systems has encouraged varying approaches to the detection and selection of visually-grounded text tokens for masking. We introduce new methods for detection of vis
Externí odkaz:
http://arxiv.org/abs/2403.03075
While most current work in multimodal machine translation (MMT) uses the Multi30k dataset for training and evaluation, we find that the resulting models overfit to the Multi30k dataset to an extreme degree. Consequently, these models perform very bad
Externí odkaz:
http://arxiv.org/abs/2403.03045
A good evaluation framework should evaluate multimodal machine translation (MMT) models by measuring 1) their use of visual information to aid in the translation task and 2) their ability to translate complex sentences such as done for text-only mach
Externí odkaz:
http://arxiv.org/abs/2403.03014
Autor:
Grigsby, Travis, Richmond, Edward
In this paper, we give a formula for the number of permutations that avoid the split patterns $3|12$ and $23|1$ with respect to a position $r$. Such permutations count the number of Schubert varieties for which the projection map from the flag variet
Externí odkaz:
http://arxiv.org/abs/2402.17654
We introduce AMAGO, an in-context Reinforcement Learning (RL) agent that uses sequence models to tackle the challenges of generalization, long-term memory, and meta-learning. Recent works have shown that off-policy learning can make in-context RL wit
Externí odkaz:
http://arxiv.org/abs/2310.09971
We present a new algorithm, Cross-Episodic Curriculum (CEC), to boost the learning efficiency and generalization of Transformer agents. Central to CEC is the placement of cross-episodic experiences into a Transformer's context, which forms the basis
Externí odkaz:
http://arxiv.org/abs/2310.08549
Autor:
Diana S. Grigsby-Toussaint, Jong Cheol Shin, Aliana Rodriguez Acevedo, William Kemball-Cook, Diane Story, Abby Katz, Ugoji Nwanaji-Enwerem, Gabrielle Evans, Azia Johnson, Brooke Ury, Yaideliz M. Romero-Ramos, Jue Yang, David M. Barker, John E. McGeary, Shira I. Dunsiger
Publikováno v:
BMC Pediatrics, Vol 24, Iss 1, Pp 1-7 (2024)
Abstract Background The prevention of pediatric mental health disorders is a growing health priority in the United States. While exposure to green space, such as outdoor vegetation, has been linked with improved mental health outcomes in children, li
Externí odkaz:
https://doaj.org/article/45baa70babc6442480bc6a6df17e7080
