Zobrazeno 1 - 10
of 11 564
pro vyhledávání: '"P. A. Lyle"'
Autor:
Busch, Alexandra N., Budzinski, Roberto C., Pasini, Federico W., Mináč, Ján, Michaels, Jonathan A., Roussy, Megan, Gulli, Roberto A., Corrigan, Ben C., Pruszynski, J. Andrew, Martinez-Trujillo, Julio, Muller, Lyle E.
Recent advances in neural recording technology allow simultaneously recording action potentials from hundreds to thousands of neurons in awake, behaving animals. However, characterizing spike patterns in the resulting data, and linking these patterns
Externí odkaz:
http://arxiv.org/abs/2412.03804
Autor:
Liu, Tingting, Giorgi, Salvatore, Aich, Ankit, Lahnala, Allison, Curtis, Brenda, Ungar, Lyle, Sedoc, João
As AI chatbots become more human-like by incorporating empathy, understanding user-centered perceptions of chatbot empathy and its impact on conversation quality remains essential yet under-explored. This study examines how chatbot identity and perce
Externí odkaz:
http://arxiv.org/abs/2411.12877
Autor:
Ratzlaff, Neale, Olson, Matthew Lyle, Hinck, Musashi, Aflalo, Estelle, Tseng, Shao-Yen, Lal, Vasudev, Howard, Phillip
Large Multi-Modal Models (LMMs) have demonstrated impressive capabilities as general-purpose chatbots that can engage in conversations about a provided input, such as an image. However, their responses are influenced by societal biases present in the
Externí odkaz:
http://arxiv.org/abs/2411.12590
Autor:
D'Orazio, Ryan, Vucetic, Danilo, Liu, Zichu, Kim, Junhyung Lyle, Mitliagkas, Ioannis, Gidel, Gauthier
Deep learning has proven to be effective in a wide variety of loss minimization problems. However, many applications of interest, like minimizing projected Bellman error and min-max optimization, cannot be modelled as minimizing a scalar loss functio
Externí odkaz:
http://arxiv.org/abs/2411.05228
Autor:
Galashov, Alexandre, Titsias, Michalis K., György, András, Lyle, Clare, Pascanu, Razvan, Teh, Yee Whye, Sahani, Maneesh
Publikováno v:
NeurIPS 2024
Neural networks are traditionally trained under the assumption that data come from a stationary distribution. However, settings which violate this assumption are becoming more popular; examples include supervised learning under distributional shifts,
Externí odkaz:
http://arxiv.org/abs/2411.04034
Autor:
Helfer, Thomas, Edwards, Thomas D. P., Dafflon, Jessica, Wong, Kaze W. K., Olson, Matthew Lyle
Generating high-resolution simulations is key for advancing our understanding of one of the universe's most violent events: Black Hole mergers. However, generating Black Hole simulations is limited by prohibitive computational costs and scalability i
Externí odkaz:
http://arxiv.org/abs/2411.02453
Autor:
Ratzlaff, Neale, Olson, Matthew Lyle, Hinck, Musashi, Tseng, Shao-Yen, Lal, Vasudev, Howard, Phillip
Large Vision Language Models (LVLMs) such as LLaVA have demonstrated impressive capabilities as general-purpose chatbots that can engage in conversations about a provided input image. However, their responses are influenced by societal biases present
Externí odkaz:
http://arxiv.org/abs/2410.13976
Autor:
Jin, Helen, Havaldar, Shreya, Kim, Chaehyeon, Xue, Anton, You, Weiqiu, Qu, Helen, Gatti, Marco, Hashimoto, Daniel A, Jain, Bhuvnesh, Madani, Amin, Sako, Masao, Ungar, Lyle, Wong, Eric
Feature-based methods are commonly used to explain model predictions, but these methods often implicitly assume that interpretable features are readily available. However, this is often not the case for high-dimensional data, and it can be hard even
Externí odkaz:
http://arxiv.org/abs/2409.13684
There is now substantial evidence for traveling waves and other structured spatiotemporal recurrent neural dynamics in cortical structures; but these observations have typically been difficult to reconcile with notions of topographically organized se
Externí odkaz:
http://arxiv.org/abs/2409.13669
We study the problem of finding curves of minimum pointwise-maximum arc-length derivative of curvature, here simply called curves of minimax spirality, among planar curves of fixed length with prescribed endpoints and tangents at the endpoints. We co
Externí odkaz:
http://arxiv.org/abs/2409.08644