Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Everett, Katie"'
Autor:
Everett, Katie, Xiao, Lechao, Wortsman, Mitchell, Alemi, Alexander A., Novak, Roman, Liu, Peter J., Gur, Izzeddin, Sohl-Dickstein, Jascha, Kaelbling, Leslie Pack, Lee, Jaehoon, Pennington, Jeffrey
Robust and effective scaling of models from small to large width typically requires the precise adjustment of many algorithmic and architectural details, such as parameterization and optimizer choices. In this work, we propose a new perspective on pa
Externí odkaz:
http://arxiv.org/abs/2407.05872
Autor:
Lachapelle, Sébastien, López, Pau Rodríguez, Sharma, Yash, Everett, Katie, Priol, Rémi Le, Lacoste, Alexandre, Lacoste-Julien, Simon
This work introduces a novel principle for disentanglement we call mechanism sparsity regularization, which applies when the latent factors of interest depend sparsely on observed auxiliary variables and/or past latent factors. We propose a represent
Externí odkaz:
http://arxiv.org/abs/2401.04890
Autor:
Wortsman, Mitchell, Liu, Peter J., Xiao, Lechao, Everett, Katie, Alemi, Alex, Adlam, Ben, Co-Reyes, John D., Gur, Izzeddin, Kumar, Abhishek, Novak, Roman, Pennington, Jeffrey, Sohl-dickstein, Jascha, Xu, Kelvin, Lee, Jaehoon, Gilmer, Justin, Kornblith, Simon
Teams that have trained large Transformer-based models have reported training instabilities at large scale that did not appear when training with the same hyperparameters at smaller scales. Although the causes of such instabilities are of scientific
Externí odkaz:
http://arxiv.org/abs/2309.14322
Autor:
Hu, Edward J., Malkin, Nikolay, Jain, Moksh, Everett, Katie, Graikos, Alexandros, Bengio, Yoshua
Latent variable models (LVMs) with discrete compositional latents are an important but challenging setting due to a combinatorially large number of possible configurations of the latents. A key tradeoff in modeling the posteriors over latents is betw
Externí odkaz:
http://arxiv.org/abs/2302.06576
Autor:
Malkin, Nikolay, Lahlou, Salem, Deleu, Tristan, Ji, Xu, Hu, Edward, Everett, Katie, Zhang, Dinghuai, Bengio, Yoshua
This paper builds bridges between two families of probabilistic algorithms: (hierarchical) variational inference (VI), which is typically used to model distributions over continuous spaces, and generative flow networks (GFlowNets), which have been us
Externí odkaz:
http://arxiv.org/abs/2210.00580
Autor:
Tuckett, Quenton M., Hill, Jeffrey E., Everett, Katie, Goodman, Colin, Wooley, Emily S., Durland Donahou, Allison, Lapham, Lauren, Buckman, Katherine, Johnson, Steve, Romagosa, Christina
Publikováno v:
In Journal of Thermal Biology July 2024 123
Autor:
Lachapelle, Sébastien, López, Pau Rodríguez, Sharma, Yash, Everett, Katie, Priol, Rémi Le, Lacoste, Alexandre, Lacoste-Julien, Simon
This work introduces a novel principle we call disentanglement via mechanism sparsity regularization, which can be applied when the latent factors of interest depend sparsely on past latent factors and/or observed auxiliary variables. We propose a re
Externí odkaz:
http://arxiv.org/abs/2107.10098
Autor:
Bavadekar, Shailesh, Dai, Andrew, Davis, John, Desfontaines, Damien, Eckstein, Ilya, Everett, Katie, Fabrikant, Alex, Flores, Gerardo, Gabrilovich, Evgeniy, Gadepalli, Krishna, Glass, Shane, Huang, Rayman, Kamath, Chaitanya, Kraft, Dennis, Kumok, Akim, Marfatia, Hinali, Mayer, Yael, Miller, Benjamin, Pearce, Adam, Perera, Irippuge Milinda, Ramachandran, Venky, Raman, Karthik, Roessler, Thomas, Shafran, Izhak, Shekel, Tomer, Stanton, Charlotte, Stimes, Jacob, Sun, Mimi, Wellenius, Gregory, Zoghi, Masrour
This report describes the aggregation and anonymization process applied to the initial version of COVID-19 Search Trends symptoms dataset (published at https://goo.gle/covid19symptomdataset on September 2, 2020), a publicly available dataset that sho
Externí odkaz:
http://arxiv.org/abs/2009.01265
Autor:
Everett, Katie, Fischer, Ian
In the causal learning setting, we wish to learn cause-and-effect relationships between variables such that we can correctly infer the effect of an intervention. While the difference between a cyclic structure and an acyclic structure may be just a s
Externí odkaz:
http://arxiv.org/abs/2007.12335
Autor:
Everett, Katie Elizabeth
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2013.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 27-28).
Previous research has sho
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 27-28).
Previous research has sho
Externí odkaz:
http://hdl.handle.net/1721.1/85416