Zobrazeno 1 - 10
of 4 583
pro vyhledávání: '"Bergsma, A."'
Several challenges make it difficult for sparse neural networks to compete with dense models. First, setting a large fraction of weights to zero impairs forward and gradient signal propagation. Second, sparse studies often need to test multiple spars
Externí odkaz:
http://arxiv.org/abs/2405.15743
Developments and applications of the OPTIMADE API for materials discovery, design, and data exchange
Autor:
Evans, Matthew L., Bergsma, Johan, Merkys, Andrius, Andersen, Casper W., Andersson, Oskar B., Beltrán, Daniel, Blokhin, Evgeny, Boland, Tara M., Balderas, Rubén Castañeda, Choudhary, Kamal, Díaz, Alberto Díaz, García, Rodrigo Domínguez, Eckert, Hagen, Eimre, Kristjan, Montero, María Elena Fuentes, Krajewski, Adam M., Mortensen, Jens Jørgen, Duarte, José Manuel Nápoles, Pietryga, Jacob, Qi, Ji, Carrillo, Felipe de Jesús Trejo, Vaitkus, Antanas, Yu, Jusong, Zettel, Adam, de Castro, Pedro Baptista, Carlsson, Johan, Cerqueira, Tiago F. T., Divilov, Simon, Hajiyani, Hamidreza, Hanke, Felix, Jose, Kevin, Oses, Corey, Riebesell, Janosh, Schmidt, Jonathan, Winston, Donald, Xie, Christen, Yang, Xiaoyu, Bonella, Sara, Botti, Silvana, Curtarolo, Stefano, Draxl, Claudia, Cobas, Luis Edmundo Fuentes, Hospital, Adam, Liu, Zi-Kui, Marques, Miguel A. L., Marzari, Nicola, Morris, Andrew J., Ong, Shyue Ping, Orozco, Modesto, Persson, Kristin A., Thygesen, Kristian S., Wolverton, Chris, Scheidgen, Markus, Toher, Cormac, Conduit, Gareth J., Pizzi, Giovanni, Gražulis, Saulius, Rignanese, Gian-Marco, Armiento, Rickard
The Open Databases Integration for Materials Design (OPTIMADE) application programming interface (API) empowers users with holistic access to a growing federation of databases, enhancing the accessibility and discoverability of materials and chemical
Externí odkaz:
http://arxiv.org/abs/2402.00572
Publikováno v:
Proceedings of the 36th Conference on Neural Information Processing Systems (NeurIPS 2022)
We present coarse-to-fine autoregressive networks (C2FAR), a method for modeling the probability distribution of univariate, numeric random variables. C2FAR generates a hierarchical, coarse-to-fine discretization of a variable autoregressively; progr
Externí odkaz:
http://arxiv.org/abs/2312.15002
Publikováno v:
Proceedings of 37th Conference on Neural Information Processing Systems (NeurIPS 2023)
We propose SutraNets, a novel method for neural probabilistic forecasting of long-sequence time series. SutraNets use an autoregressive generative model to factorize the likelihood of long sequences into products of conditional probabilities. When ge
Externí odkaz:
http://arxiv.org/abs/2312.14880
Deep learning models have become widely adopted in various domains, but their performance heavily relies on a vast amount of data. Datasets often contain a large number of irrelevant or redundant samples, which can lead to computational inefficiencie
Externí odkaz:
http://arxiv.org/abs/2309.11922
Autor:
Ishida, Sahoko, Bergsma, Wicher
This paper focuses on interpretable additive Gaussian process (GP) regression and its efficient implementation for large-scale data with a multi-dimensional grid structure, as commonly encountered in spatio-temporal analysis. A popular and scalable a
Externí odkaz:
http://arxiv.org/abs/2305.07073
Autor:
Bergsma, Fenna, author
Publikováno v:
The Place of Case in Grammar, 2024.
Externí odkaz:
https://doi.org/10.1093/oso/9780198865926.003.0013
Autor:
Rudas, Tamas, Bergsma, Wicher
Marginal models involve restrictions on the conditional and marginal association structure of a set of categorical variables. They generalize log-linear models for contingency tables, which are the fundamental tools for modelling the conditional asso
Externí odkaz:
http://arxiv.org/abs/2304.03380
Autor:
Tegan A. Otto, Tessa Bergsma, Maurice Dekker, Sara N. Mouton, Paola Gallardo, Justina C. Wolters, Anton Steen, Patrick R. Onck, Liesbeth M. Veenhoff
Publikováno v:
Cell Reports, Vol 43, Iss 10, Pp 114793- (2024)
Summary: Transport through the nuclear pore complex (NPC) relies on intrinsically disordered FG-nucleoporins (FG-Nups) forming a selective barrier. Away from the NPC, FG-Nups readily form condensates and aggregates, and we address how this behavior i
Externí odkaz:
https://doaj.org/article/e1eeaf9c4b9a47fe8aeb7b056514bfad
Autor:
Bergsma, Erwin W. J.1 (AUTHOR) erwin.bergsma@cnes.fr, Klotz, Adrien N.1,2 (AUTHOR) rafael.almar@ird.fr, Artigues, Stéphanie1 (AUTHOR) marcan.graffin@ird.fr, Graffin, Marcan1,2 (AUTHOR) annaprenowitz@gmail.com, Prenowitz, Anna1 (AUTHOR) jean-marc.delvit@cnes.fr, Delvit, Jean-Marc1 (AUTHOR), Almar, Rafael2 (AUTHOR)
Publikováno v:
Remote Sensing. Aug2024, Vol. 16 Issue 15, p2795. 18p.