AUTURNAL / RESEARCH SOURCES
Fuentes de referencia
Referencias primarias de la colección. Los títulos y datos bibliográficos conservan su idioma original.
Referencias 481–504 de 766
OAuth 2.0 Token Introspection
Justin RicherAbrir fuente original ↗
2015OAuth 2.0 Token Revocation
Torsten Lodderstedt; Stefanie Dronia; Marius ScurtescuAbrir fuente original ↗
2013ObliviStore: High Performance Oblivious Distributed Cloud Data Store - Extended Abstract
Emil Stefanov; Elaine ShiAbrir fuente original ↗
2013Observation of high-energy neutrinos from the Galactic plane
IceCube Collaboration*†; R. Abbasi; M. Ackermann; J. Adams; J. A. Aguilar; M. Ahlers; et al.
2023-06-30Ubicación en la fuente: Abstract; diffuse-template likelihood
Alcance de la consulta: 银河面弥散统计证据,不等于逐个源定位。
Abrir fuente original ↗Citado en (1)
Observation of spatial charge and spin correlations in the 2D Fermi-Hubbard model
Lawrence W. Cheuk; Matthew A. Nichols; Katherine R. Lawrence; Melih Okan; Hao Zhang; Ehsan Khatami; Nandini Trivedi; Thereza Paiva; Marcos Rigol; Martin W. ZwierleinAbrir fuente original ↗
2016Observation-based early-warning signals for a collapse of the Atlantic Meridional Overturning Circulation
Niklas BoersAbrir fuente original ↗
2021Off-Policy Deep Reinforcement Learning without Exploration
Scott Fujimoto; David Meger; Doina PrecupAbrir fuente original ↗
2019Offline Reinforcement Learning with Implicit Q-Learning
Ilya Kostrikov; Ashvin Nair; Sergey LevineAbrir fuente original ↗
2021Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems
Sergey Levine; Aviral Kumar; George Tucker; Justin FuAbrir fuente original ↗
2020On Calibration of Modern Neural Networks
Chuan Guo; Geoff Pleiss; Yu Sun; Kilian Q. WeinbergerAbrir fuente original ↗
2017Citado en (1)
On Degeneracies in Retrievals of Exoplanetary Transmission Spectra
Luis Welbanks; Nikku MadhusudhanAbrir fuente original ↗
2019On instabilities of deep learning in image reconstruction and the potential costs of AI
Vegard Antun; Francesco Renna; Clarice Poon; Ben Adcock; Anders C. HansenAbrir fuente original ↗
2020On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima
Nitish Shirish Keskar; Dheevatsa Mudigere; Jorge Nocedal; Mikhail Smelyanskiy; Ping Tak Peter TangAbrir fuente original ↗
2017On Lazy Training in Differentiable Programming
Lénaïc Chizat; Edouard Oyallon; Francis BachAbrir fuente original ↗
2019On the Bottleneck of Graph Neural Networks and its Practical Implications
Uri Alon; Eran YahavAbrir fuente original ↗
2021Citado en (1)
On the detection of a cosmic dawn signal in the radio background
Saurabh Singh; Jishnu Nambissan T.; Ravi Subrahmanyan; N. Udaya Shankar; B. S. Girish; A. Raghunathan; R. Somashekar; K. S. Srivani; Mayuri Sathyanarayana RaoAbrir fuente original ↗
2022On the Global Convergence of Gradient Descent for Over-parameterized Models using Optimal Transport
Lénaïc Chizat; Francis BachAbrir fuente original ↗
2018On the Limitations of Multimodal VAEs
Imant Daunhawer; Thomas M. Sutter; Kieran Chin-Cheong; Emanuele Palumbo; Julia E. VogtAbrir fuente original ↗
2021On the Locality of Codeword Symbols
Parikshit Gopalan; Cheng Huang; Huseyin Simitci; Sergey YekhaninAbrir fuente original ↗
2012On The Power of Curriculum Learning in Training Deep Networks
Guy Hacohen; Daphna WeinshallAbrir fuente original ↗
2019Citado en (1)
On the Size of Pairing-Based Non-interactive Arguments
Jens GrothAbrir fuente original ↗
2016On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes
Rishabh Agarwal; Nino Vieillard; Yongchao Zhou; Piotr Stanczyk; Sabela Ramos; Matthieu Geist; Olivier BachemAbrir fuente original ↗
2023One-step Diffusion with Distribution Matching Distillation
Tianwei Yin; Michaël Gharbi; Richard Zhang; Eli Shechtman; Fredo Durand; William T. Freeman; Taesung ParkAbrir fuente original ↗
2024Optimizing and Evaluating Transient Gradual Typing
Michael M. Vitousek; Jeremy G. Siek; Avik ChaudhuriAbrir fuente original ↗
2019