Zobrazeno 1 - 10
of 11 570
pro vyhledávání: '"Gilpin, A. A."'
Autor:
Liu, Li, Yang, Diji, Zhong, Sijia, Tholeti, Kalyana Suma Sree, Ding, Lei, Zhang, Yi, Gilpin, Leilani H.
In question-answering scenarios, humans can assess whether the available information is sufficient and seek additional information if necessary, rather than providing a forced answer. In contrast, Vision Language Models (VLMs) typically generate dire
Externí odkaz:
http://arxiv.org/abs/2411.00394
Autor:
Zhang, Yuanzhao, Gilpin, William
Time-series forecasting is a challenging problem that traditionally requires specialized models custom-trained for the specific task at hand. Recently, inspired by the success of large language models, foundation models pre-trained on vast amounts of
Externí odkaz:
http://arxiv.org/abs/2409.15771
Publikováno v:
Springer, Lecture Notes on Computer Science (LNAI,volume 14980), 2024
Neurosymbolic approaches can add robustness to opaque neural systems by incorporating explainable symbolic representations. However, previous approaches have not used formal logic to contextualize queries to and validate outputs of large language mod
Externí odkaz:
http://arxiv.org/abs/2409.11589
Autor:
Morris, Jonathan Wellington, Shah, Vishrut, Besanceney, Alex, Shah, Daksh, Gilpin, Leilani H.
Sim-to real gap in Reinforcement Learning is when a model trained in a simulator does not translate to the real world. This is a problem for Autonomous Vehicles (AVs) as vehicle dynamics can vary from simulation to reality, and also from vehicle to v
Externí odkaz:
http://arxiv.org/abs/2409.10532
Autor:
Rancurel, Belén Alonso, Cao, Son, Carroll, Thomas J., Castellan, Rhys, Catano-Mur, Erika, Cesar, John P., Coelho, João A. B., Dills, Patrick, Dodwell, Thomas, Edmondson, Jack, van Eijk, Daan, Fetterly, Quinn, Garbal, Zoé, Germani, Stefano, Gilpin, Thomas, Giraudo, Anthony, Habig, Alec, Hanuska, Daniel, Hausner, Harry, Hernandez, Wilson Y., Holin, Anna, Huang, Junting, Jones, Sebastian B., Karle, Albrecht, Kileff, George, Jenkins, Kai R., Kooijman, Paul, Kreymer, Arthur, LaFond, Gabe M., Lang, Karol, Lazar, Jeffrey P., Li, Rui, Liu, Kexin, Loving, David A., Mánek, Petr, Marshak, Marvin L., Meier, Jerry R., Miller, William, Nelson, Jeffrey K., Ng, Christopher, Nichol, Ryan J., Paolone, Vittorio, Perch, Andrew, Pfützner, Maciej M., Radovic, Alexander, Rawlins, Katherine, Roedl, Patrick, Rogers, Lucas, Safa, Ibrahim, Sousa, Alexandre, Tingey, Josh, Thomas, Jennifer, Trokan-Tenorio, Jozef, Vahle, Patricia, Wade, Richard, Wendt, Christopher, Wendt, Daniel, Whitehead, Leigh H., Wolcott, Samuel, Yuan, Tianlu
The CHIPS R&D project focuses on development of low-cost water Cherenkov neutrino detectors through novel design strategies and resourceful engineering. This work presents an end-to-end DAQ solution intended for a recent 5 kt CHIPS prototype, which i
Externí odkaz:
http://arxiv.org/abs/2408.10828
Autonomous driving demands an integrated approach that encompasses perception, prediction, and planning, all while operating under strict energy constraints to enhance scalability and environmental sustainability. We present Spiking Autonomous Drivin
Externí odkaz:
http://arxiv.org/abs/2405.19687
Autor:
Gilpin, William
Living systems operate far from equilibrium, yet few general frameworks provide global bounds on biological transients. Here, we frame equilibration in complex ecosystems as the process of solving an analogue optimization problem. We show that functi
Externí odkaz:
http://arxiv.org/abs/2403.19186
Autor:
Rancurel, B. Alonso, Angelides, N., Augustoni, G., Bash, S., Bergmann, B., Bertschinger, N., Bizouard, P., Campbell, M., Cao, S., Carroll, T. J., Castellan, R., Catano-Mur, E., Cesar, J. P., Coelho, J. A. B., Dills, P., Dodwell, T., Edmondson, J., van Eijk, D., Fetterly, Q., Garbal, Z., Germani, S., Gilpin, T., Giraudo, A., Habig, A., Hanuska, D., Hausner, H., Hernandez, W. Y., Holin, A., Huang, J., Jones, S. B., Karle, A., Kileff, G., Jenkins, K. R., Kooijman, P., Kreymer, A., Loving, D. A., LaFond, G. M., Lang, K., Lazar, J. P., Li, R., Liu, K., Mánek, P., Marshak, M. L., Meier, J. R., Miller, W., Nelson, J. K., Ng, C., Nichol, R. J., Paolone, V., Perch, A., Pfützner, M. M., Radovic, A., Rawlins, K., Roedl, P., Rogers, L., Safa, I., Sousa, A., Tingey, J., Thomas, J., Trokan-Tenorio, J., Vahle, P., Wade, R., Wendt, C., Wendt, D., Whitehead, L. H., Wolcott, S., Yuan, T.
CHIPS (CHerenkov detectors In mine PitS) was a prototype large-scale water Cherenkov detector located in northern Minnesota. The main aim of the R&D project was to demonstrate that construction costs of neutrino oscillation detectors could be reduced
Externí odkaz:
http://arxiv.org/abs/2401.11728
Autor:
Mitra, Shreyan, Gilpin, Leilani
Explanatory systems make the behavior of machine learning models more transparent, but are often inconsistent. To quantify the differences between explanatory systems, this paper presents the Shreyan Distance, a novel metric based on the weighted dif
Externí odkaz:
http://arxiv.org/abs/2311.10811
Autor:
Gilpin, William
Publikováno v:
Nature Reviews Physics, 2024
Modern generative machine learning models demonstrate surprising ability to create realistic outputs far beyond their training data, such as photorealistic artwork, accurate protein structures, or conversational text. These successes suggest that gen
Externí odkaz:
http://arxiv.org/abs/2311.04128