AUTURNAL / RESEARCH SOURCES

参考文献

研究集で引用した一次資料です。照合しやすいよう、題名と書誌情報は原文を保持しています。

全766件中 481–504件

OAuth 2.0 Token Introspection
Justin Richer
2015
一次資料を開く ↗
引用したレビュー (1)
- Permission Has a Time: Relationship-Based Authorization and Consistent Revocation
OAuth 2.0 Token Revocation
Torsten Lodderstedt; Stefanie Dronia; Marius Scurtescu
2013
一次資料を開く ↗
引用したレビュー (1)
- Permission Has a Time: Relationship-Based Authorization and Consistent Revocation
ObliviStore: High Performance Oblivious Distributed Cloud Data Store - Extended Abstract
Emil Stefanov; Elaine Shi
2013
一次資料を開く ↗
引用したレビュー (1)
- Hiding the Address: Oblivious RAM, Leakage, and the Cost of Access Privacy
Observation of high-energy neutrinos from the Galactic plane
IceCube Collaboration*†; R. Abbasi; M. Ackermann; J. Adams; J. A. Aguilar; M. Ahlers; et al.
2023-06-30
参照箇所: Abstract; diffuse-template likelihood
確認範囲: 银河面弥散统计证据，不等于逐个源定位。
一次資料を開く ↗
引用したレビュー (1)
- 一条粒子轨迹指向哪里：中微子来源、多信使关联与全局显著性
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. Zwierlein
2016
一次資料を開く ↗
引用したレビュー (1)
- Learning from an Artificial Lattice: What Fermi-Hubbard Quantum Simulators Actually Measure
Observation-based early-warning signals for a collapse of the Atlantic Meridional Overturning Circulation
Niklas Boers
2021
一次資料を開く ↗
引用したレビュー (1)
- Reading an Ocean Circulation: AMOC Observations, Proxy Ambiguity and Early-Warning Claims
Off-Policy Deep Reinforcement Learning without Exploration
Scott Fujimoto; David Meger; Doina Precup
2019
一次資料を開く ↗
引用したレビュー (1)
- The Action Missing from the Dataset: Support, Pessimism, and Identification in Offline Deep Reinforcement Learning
Offline Reinforcement Learning with Implicit Q-Learning
Ilya Kostrikov; Ashvin Nair; Sergey Levine
2021
一次資料を開く ↗
引用したレビュー (1)
- The Action Missing from the Dataset: Support, Pessimism, and Identification in Offline Deep Reinforcement Learning
Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems
Sergey Levine; Aviral Kumar; George Tucker; Justin Fu
2020
一次資料を開く ↗
引用したレビュー (1)
- The Action Missing from the Dataset: Support, Pessimism, and Identification in Offline Deep Reinforcement Learning
On Calibration of Modern Neural Networks
Chuan Guo; Geoff Pleiss; Yu Sun; Kilian Q. Weinberger
2017
一次資料を開く ↗
引用したレビュー (1)
- Calibrated Probabilities Are Not Yet Good Decisions
On Degeneracies in Retrievals of Exoplanetary Transmission Spectra
Luis Welbanks; Nikku Madhusudhan
2019
一次資料を開く ↗
引用したレビュー (1)
- An Atmosphere through a Spectrum: Clouds, Stellar Contamination and Exoplanet Retrieval
On instabilities of deep learning in image reconstruction and the potential costs of AI
Vegard Antun; Francesco Renna; Clarice Poon; Ben Adcock; Anders C. Hansen
2020
一次資料を開く ↗
引用したレビュー (1)
- A Plausible Image Is Not a Measurement: Learned MRI Reconstruction and Data Consistency
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima
Nitish Shirish Keskar; Dheevatsa Mudigere; Jorge Nocedal; Mikhail Smelyanskiy; Ping Tak Peter Tang
2017
一次資料を開く ↗
引用したレビュー (1)
- The Same Predictor, a Sharper Minimum: Parameter Symmetry and the Meaning of Loss Geometry
On Lazy Training in Differentiable Programming
Lénaïc Chizat; Edouard Oyallon; Francis Bach
2019
一次資料を開く ↗
引用したレビュー (1)
- Beyond a Frozen Tangent: What Kernel Limits Explain about Neural Feature Learning
On the Bottleneck of Graph Neural Networks and its Practical Implications
Uri Alon; Eran Yahav
2021
一次資料を開く ↗
引用したレビュー (1)
- Graph Depth, Smoothing, and the Loss of Distinctions
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 Rao
2022
一次資料を開く ↗
引用したレビュー (1)
- Listening beneath the Foreground: Calibration and Identifiability in Cosmic-Dawn Radio Experiments
On the Global Convergence of Gradient Descent for Over-parameterized Models using Optimal Transport
Lénaïc Chizat; Francis Bach
2018
一次資料を開く ↗
引用したレビュー (1)
- Beyond a Frozen Tangent: What Kernel Limits Explain about Neural Feature Learning
On the Limitations of Multimodal VAEs
Imant Daunhawer; Thomas M. Sutter; Kieran Chin-Cheong; Emanuele Palumbo; Julia E. Vogt
2021
一次資料を開く ↗
引用したレビュー (1)
- When a Sensor Is Missing: Multimodal Learning and Identifiability
On the Locality of Codeword Symbols
Parikshit Gopalan; Cheng Huang; Huseyin Simitci; Sergey Yekhanin
2012
一次資料を開く ↗
引用したレビュー (1)
- Erasure Coding in Real Storage Systems: Durability, Locality, and Repair Traffic
On The Power of Curriculum Learning in Training Deep Networks
Guy Hacohen; Daphna Weinshall
2019
一次資料を開く ↗
引用したレビュー (1)
- A Curriculum Is Also a Sampling Policy
On the Size of Pairing-Based Non-interactive Arguments
Jens Groth
2016
一次資料を開く ↗
引用したレビュー (1)
- Succinct Proofs, Substantial Costs: Evaluating Zero-Knowledge Systems End to End
On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes
Rishabh Agarwal; Nino Vieillard; Yongchao Zhou; Piotr Stanczyk; Sabela Ramos; Matthieu Geist; Olivier Bachem
2023
一次資料を開く ↗
引用したレビュー (1)
- Recursive Synthetic Data and the Fate of Rare Support
One-step Diffusion with Distribution Matching Distillation
Tianwei Yin; Michaël Gharbi; Richard Zhang; Eli Shechtman; Fredo Durand; William T. Freeman; Taesung Park
2024
一次資料を開く ↗
引用したレビュー (1)
- One Step Is a Budget, Not a Distribution: Consistency Models and the Evidence for Fast Generation
Optimizing and Evaluating Transient Gradual Typing
Michael M. Vitousek; Jeremy G. Siek; Avik Chaudhuri
2019
一次資料を開く ↗
引用したレビュー (1)
- Types at the Boundary: Gradual Guarantees, Blame, and the Cost of Enforcement

参考文献

OAuth 2.0 Token Introspection

OAuth 2.0 Token Revocation

ObliviStore: High Performance Oblivious Distributed Cloud Data Store - Extended Abstract

Observation of high-energy neutrinos from the Galactic plane

Observation of spatial charge and spin correlations in the 2D Fermi-Hubbard model

Observation-based early-warning signals for a collapse of the Atlantic Meridional Overturning Circulation

Off-Policy Deep Reinforcement Learning without Exploration

Offline Reinforcement Learning with Implicit Q-Learning

Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems

On Calibration of Modern Neural Networks

On Degeneracies in Retrievals of Exoplanetary Transmission Spectra

On instabilities of deep learning in image reconstruction and the potential costs of AI

On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima

On Lazy Training in Differentiable Programming

On the Bottleneck of Graph Neural Networks and its Practical Implications

On the detection of a cosmic dawn signal in the radio background

On the Global Convergence of Gradient Descent for Over-parameterized Models using Optimal Transport

On the Limitations of Multimodal VAEs

On the Locality of Codeword Symbols

On The Power of Curriculum Learning in Training Deep Networks

On the Size of Pairing-Based Non-interactive Arguments

On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes

One-step Diffusion with Distribution Matching Distillation

Optimizing and Evaluating Transient Gradual Typing