Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Ostrow, Mitchell"'
Publikováno v:
Advances in Neural Information Processing Systems 2024
Diffusion models are capable of generating photo-realistic images that combine elements which likely do not appear together in the training set, demonstrating the ability to \textit{compositionally generalize}. Nonetheless, the precise mechanism of c
Externí odkaz:
http://arxiv.org/abs/2408.13256
To generate coherent responses, language models infer unobserved meaning from their input text sequence. One potential explanation for this capability arises from theories of delay embeddings in dynamical systems, which prove that unobserved variable
Externí odkaz:
http://arxiv.org/abs/2406.11993
Autor:
Schaeffer, Rylan, Zahedi, Nika, Khona, Mikail, Pai, Dhruv, Truong, Sang, Du, Yilun, Ostrow, Mitchell, Chandra, Sarthak, Carranza, Andres, Fiete, Ila Rani, Gromov, Andrey, Koyejo, Sanmi
Associative memory and probabilistic modeling are two fundamental topics in artificial intelligence. The first studies recurrent neural networks designed to denoise, complete and retrieve data, whereas the second studies learning and sampling from pr
Externí odkaz:
http://arxiv.org/abs/2402.10202
How can we tell whether two neural networks utilize the same internal processes for a particular computation? This question is pertinent for multiple subfields of neuroscience and machine learning, including neuroAI, mechanistic interpretability, and
Externí odkaz:
http://arxiv.org/abs/2306.10168
Autor:
Ostrow, Mitchell, Fiete, Ila
Publikováno v:
Nature; Aug2024, Vol. 632 Issue 8026, p744-745, 2p
