Every paper with a summary

Every arXiv paper Paperlayer has summarized so far. Open any of them to read the summary beside the original PDF, with every point linked to the line, figure, or table it came from.

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19,081 to 19,140 of 119,954

Modified Gravity Theories on a Nutshell: Inflation, Bounce and Late-time Evolution
S. Nojiri, S. D. Odintsov, V. K. Oikonomou
gr-qcastro-ph.COhep-tharXiv:1705.11098v32017
Parametric finite element approximations of curvature driven interface evolutions
John W. Barrett, Harald Garcke, Robert Nürnberg
math.NAcs.NAarXiv:1903.09462v32019
Wide Neural Networks of Any Depth Evolve as Linear Models Under Gradient Descent
Jaehoon Lee, Lechao Xiao, Samuel S. Schoenholz +4
stat.MLcs.LGarXiv:1902.06720v42019
IBM Q Experience as a versatile experimental testbed for simulating open quantum systems
Guillermo García-Pérez, Matteo A. C. Rossi, Sabrina Maniscalco
quant-pharXiv:1906.07099v22019
Deterministic Preparation of Dicke States
Andreas Bärtschi, Stephan Eidenbenz
quant-phcs.DSarXiv:1904.07358v12019
semopy: A Python package for Structural Equation Modeling
Meshcheryakov Georgy, Igolkina Anna
stat.AParXiv:1905.09376v22019
Supervised learning with quantum enhanced feature spaces
Vojtech Havlicek, Antonio D. Córcoles, Kristan Temme +4
quant-phstat.MLarXiv:1804.11326v22018
Hybrid Block Successive Approximation for One-Sided Non-Convex Min-Max Problems: Algorithms and Applications
Songtao Lu, Ioannis Tsaknakis, Mingyi Hong +1
math.OCstat.MLarXiv:1902.08294v22019
Nonparametric inference of interaction laws in systems of agents from trajectory data
Fei Lu, Mauro Maggioni, Sui Tang +1
cs.LGstat.MLarXiv:1812.06003v42018
Quantum Generative Adversarial Networks for Learning and Loading Random Distributions
Christa Zoufal, Aurélien Lucchi, Stefan Woerner
quant-pharXiv:1904.00043v22019
Green-PoW: An Energy-Efficient Blockchain Proof-of-Work Consensus Algorithm
Noureddine Lasla, Lina Alsahan, Mohamed Abdallah +1
cs.CRarXiv:2007.04086v12020
Fine-Grained Attention Mechanism for Neural Machine Translation
Heeyoul Choi, Kyunghyun Cho, Yoshua Bengio
cs.CLarXiv:1803.11407v22018
Deep Learning for Signal Authentication and Security in Massive Internet of Things Systems
Aidin Ferdowsi, Walid Saad
cs.CRcs.GTcs.LGarXiv:1803.00916v22018
Model reduction of dynamical systems on nonlinear manifolds using deep convolutional autoencoders
Kookjin Lee, Kevin Carlberg
math.NAarXiv:1812.08373v32018
Everything is a Race and Nakamoto Always Wins
Amir Dembo, Sreeram Kannan, Ertem Nusret Tas +4
cs.CRarXiv:2005.10484v42020
Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentation
Chenxi Liu, Liang-Chieh Chen, Florian Schroff +4
cs.CVcs.LGarXiv:1901.02985v22019
Statistical field theory for neural networks
Moritz Helias, David Dahmen
cond-mat.dis-nncond-mat.stat-mecharXiv:1901.10416v12019
Balanced Excitation and Inhibition are Required for High-Capacity, Noise-Robust Neuronal Selectivity
Ran Rubin, L. F. Abbott, Haim Sompolinsky
q-bio.NCcond-mat.dis-nncs.LGarXiv:1705.01502v12017
Quantum Approximate Optimization Algorithm: Performance, Mechanism, and Implementation on Near-Term Devices
Leo Zhou, Sheng-Tao Wang, Soonwon Choi +2
quant-phcond-mat.dis-nncond-mat.stat-mecharXiv:1812.01041v22018
Technical Note on Transcription Factor Motif Discovery from Importance Scores (TF-MoDISco) version 0.5.6.5
Avanti Shrikumar, Katherine Tian, Žiga Avsec +5
cs.LGq-bio.GNstat.MLarXiv:1811.00416v52018
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data
Liu Yang, Xuhui Meng, George Em Karniadakis
stat.MLcs.LGarXiv:2003.06097v12020
Quantifying total uncertainty in physics-informed neural networks for solving forward and inverse stochastic problems
Dongkun Zhang, Lu Lu, Ling Guo +1
math.APphysics.comp-phstat.MLarXiv:1809.08327v12018
DraftAttention2: Fast Video Diffusion with Low-Resolution-Guided Mixed-Precision Attention
Rui Ding, Haopeng Li, Weize Ma +10
cs.CVcs.AIarXiv:2609.32628v12026
Centralized and distributed online learning for sparse time-varying optimization
Sophie M. Fosson
math.OCcs.LGarXiv:2001.11939v12020
Gaussian Signalling for Covert Communications
Shihao Yan, Yirui Cong, Stephen Hanly +1
cs.ITcs.CRarXiv:1807.00719v32018
Exploring Connections Between Active Learning and Model Extraction
Varun Chandrasekaran, Kamalika Chaudhuri, Irene Giacomelli +2
cs.LGcs.CRstat.MLarXiv:1811.02054v62018
Efficient Bias-Span-Constrained Exploration-Exploitation in Reinforcement Learning
Ronan Fruit, Matteo Pirotta, Alessandro Lazaric +1
cs.LGstat.MLarXiv:1802.04020v22018
On gradient regularizers for MMD GANs
Michael Arbel, Danica J. Sutherland, Mikołaj Bińkowski +1
stat.MLcs.LGarXiv:1805.11565v52018
Distributed inference for quantile regression processes
Stanislav Volgushev, Shih-Kang Chao, Guang Cheng
math.STstat.MEarXiv:1701.06088v32017
STyLuS*: A Temporal Logic Optimal Control Synthesis Algorithm for Large-Scale Multi-Robot Systems
Yiannis Kantaros, Michael M. Zavlanos
cs.ROarXiv:1809.08345v32018
Improved Few-Shot Visual Classification
Peyman Bateni, Raghav Goyal, Vaden Masrani +2
cs.CVarXiv:1912.03432v32019
Channel Modeling for Diffusive Molecular Communication - A Tutorial Review
Vahid Jamali, Arman Ahmadzadeh, Wayan Wicke +2
cs.ETarXiv:1812.05492v12018
How To Make the Gradients Small Stochastically: Even Faster Convex and Nonconvex SGD
Zeyuan Allen-Zhu
cs.LGcs.DSmath.OCarXiv:1801.02982v32018
Parallel Entangling Operations on a Universal Ion Trap Quantum Computer
C. Figgatt, A. Ostrander, N. M. Linke +4
quant-phcs.ETarXiv:1810.11948v12018
Quantum generative adversarial networks
Pierre-Luc Dallaire-Demers, Nathan Killoran
quant-phcs.LGarXiv:1804.08641v22018
Demonstration of a Reconfigurable Entangled Radiofrequency-Photonic Sensor Network
Yi Xia, Wei Li, William Clark +3
quant-phphysics.opticsarXiv:1910.08825v32019
Ultra-Reliable Low Latency Communication (URLLC) using Interface Diversity
Jimmy J. Nielsen, Rongkuan Liu, Petar Popovski
cs.ITmath.ITarXiv:1711.07771v12017
Extreme Events: Mechanisms and Prediction
Mohammad Farazmand, Themistoklis P. Sapsis
nlin.CDmath.DSphysics.ao-pharXiv:1803.06277v12018
Achieving Shrinkage in a Time-Varying Parameter Model Framework
Angela Bitto, Sylvia Frühwirth-Schnatter
stat.MEstat.APstat.COarXiv:1611.01310v22016
Gaussian Processes and Kernel Methods: A Review on Connections and Equivalences
Motonobu Kanagawa, Philipp Hennig, Dino Sejdinovic +1
stat.MLcs.LGarXiv:1807.02582v12018
Multi-Label Image Classification via Knowledge Distillation from Weakly-Supervised Detection
Yongcheng Liu, Lu Sheng, Jing Shao +3
cs.CVcs.AIcs.LGarXiv:1809.05884v22018
A Closer Look at Deep Learning Heuristics: Learning rate restarts, Warmup and Distillation
Akhilesh Gotmare, Nitish Shirish Keskar, Caiming Xiong +1
cs.LGstat.MLarXiv:1810.13243v12018
The Mirage of Action-Dependent Baselines in Reinforcement Learning
George Tucker, Surya Bhupatiraju, Shixiang Gu +3
cs.LGstat.MLarXiv:1802.10031v32018
Entangling Bosonic Modes via an Engineered Exchange Interaction
Yvonne Y. Gao, Brian J. Lester, Kevin Chou +5
quant-pharXiv:1806.07401v12018
Questaal: a package of electronic structure methods based on the linear muffin-tin orbital technique
Dimitar Pashov, Swagata Acharya, Walter R. L. Lambrecht +5
cond-mat.mtrl-scicond-mat.str-elarXiv:1907.06021v22019
Rethinking Knowledge Graph Propagation for Zero-Shot Learning
Michael Kampffmeyer, Yinbo Chen, Xiaodan Liang +3
cs.CVarXiv:1805.11724v32018
Discovering Phases, Phase Transitions and Crossovers through Unsupervised Machine Learning: A critical examination
Wenjian Hu, Rajiv R. P. Singh, Richard T. Scalettar
cond-mat.stat-mecharXiv:1704.00080v22017
Adaptive pooling operators for weakly labeled sound event detection
Brian McFee, Justin Salamon, Juan Pablo Bello
cs.SDcs.LGeess.ASarXiv:1804.10070v22018
Massive MIMO with Spatially Correlated Rician Fading Channels
Özgecan Özdogan, Emil Björnson, Erik G. Larsson
cs.ITarXiv:1805.07972v22018
Neural Network Renormalization Group
Shuo-Hui Li, Lei Wang
cond-mat.stat-mechcs.LGstat.MLarXiv:1802.02840v42018
Bridging the Gap Between Safety and Real-Time Performance in Receding-Horizon Trajectory Design for Mobile Robots
Shreyas Kousik, Sean Vaskov, Fan Bu +2
cs.ROcs.SYeess.SYarXiv:1809.06746v22018
Quantum Image Processing and Its Application to Edge Detection: Theory and Experiment
Xi-Wei Yao, Hengyan Wang, Zeyang Liao +12
quant-pharXiv:1801.01465v12018
The Tensor Networks Anthology: Simulation techniques for many-body quantum lattice systems
Pietro Silvi, Ferdinand Tschirsich, Matthias Gerster +4
quant-pharXiv:1710.03733v22017
A Mean Field View of the Landscape of Two-Layers Neural Networks
Song Mei, Andrea Montanari, Phan-Minh Nguyen
stat.MLcond-mat.stat-mechcs.LGarXiv:1804.06561v22018
Generative Modeling using the Sliced Wasserstein Distance
Ishan Deshpande, Ziyu Zhang, Alexander Schwing
cs.CVarXiv:1803.11188v12018
Computational Optimal Transport
Gabriel Peyré, Marco Cuturi
stat.MLarXiv:1803.00567v42018
Efficient Exploration via State Marginal Matching
Lisa Lee, Benjamin Eysenbach, Emilio Parisotto +3
cs.LGcs.AIcs.ROarXiv:1906.05274v32019
The quantum Rabi model: solution and dynamics
Qiongtao Xie, Honghua Zhong, Murray T. Batchelor +1
quant-phphysics.atom-pharXiv:1609.00434v32016
Deep Neural Networks as Gaussian Processes
Jaehoon Lee, Yasaman Bahri, Roman Novak +3
stat.MLcs.LGarXiv:1711.00165v32017
Gaussian Differential Privacy
Jinshuo Dong, Aaron Roth, Weijie J. Su
cs.LGcs.CRcs.DSarXiv:1905.02383v32019

Every paper with a summary

Modified Gravity Theories on a Nutshell: Inflation, Bounce and Late-time Evolution

Parametric finite element approximations of curvature driven interface evolutions

Wide Neural Networks of Any Depth Evolve as Linear Models Under Gradient Descent

IBM Q Experience as a versatile experimental testbed for simulating open quantum systems

Deterministic Preparation of Dicke States

semopy: A Python package for Structural Equation Modeling

Supervised learning with quantum enhanced feature spaces

Hybrid Block Successive Approximation for One-Sided Non-Convex Min-Max Problems: Algorithms and Applications

Nonparametric inference of interaction laws in systems of agents from trajectory data

Quantum Generative Adversarial Networks for Learning and Loading Random Distributions

Green-PoW: An Energy-Efficient Blockchain Proof-of-Work Consensus Algorithm

Fine-Grained Attention Mechanism for Neural Machine Translation

Deep Learning for Signal Authentication and Security in Massive Internet of Things Systems

Model reduction of dynamical systems on nonlinear manifolds using deep convolutional autoencoders

Everything is a Race and Nakamoto Always Wins

Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentation

Statistical field theory for neural networks

Balanced Excitation and Inhibition are Required for High-Capacity, Noise-Robust Neuronal Selectivity

Quantum Approximate Optimization Algorithm: Performance, Mechanism, and Implementation on Near-Term Devices

Technical Note on Transcription Factor Motif Discovery from Importance Scores (TF-MoDISco) version 0.5.6.5

B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data

Quantifying total uncertainty in physics-informed neural networks for solving forward and inverse stochastic problems

DraftAttention2: Fast Video Diffusion with Low-Resolution-Guided Mixed-Precision Attention

Centralized and distributed online learning for sparse time-varying optimization

Gaussian Signalling for Covert Communications

Exploring Connections Between Active Learning and Model Extraction

Efficient Bias-Span-Constrained Exploration-Exploitation in Reinforcement Learning

On gradient regularizers for MMD GANs

Distributed inference for quantile regression processes

STyLuS*: A Temporal Logic Optimal Control Synthesis Algorithm for Large-Scale Multi-Robot Systems

Improved Few-Shot Visual Classification

Channel Modeling for Diffusive Molecular Communication - A Tutorial Review

How To Make the Gradients Small Stochastically: Even Faster Convex and Nonconvex SGD

Parallel Entangling Operations on a Universal Ion Trap Quantum Computer

Quantum generative adversarial networks

Demonstration of a Reconfigurable Entangled Radiofrequency-Photonic Sensor Network

Ultra-Reliable Low Latency Communication (URLLC) using Interface Diversity

Extreme Events: Mechanisms and Prediction

Achieving Shrinkage in a Time-Varying Parameter Model Framework

Gaussian Processes and Kernel Methods: A Review on Connections and Equivalences

Multi-Label Image Classification via Knowledge Distillation from Weakly-Supervised Detection

A Closer Look at Deep Learning Heuristics: Learning rate restarts, Warmup and Distillation

The Mirage of Action-Dependent Baselines in Reinforcement Learning

Entangling Bosonic Modes via an Engineered Exchange Interaction

Questaal: a package of electronic structure methods based on the linear muffin-tin orbital technique

Rethinking Knowledge Graph Propagation for Zero-Shot Learning

Discovering Phases, Phase Transitions and Crossovers through Unsupervised Machine Learning: A critical examination

Adaptive pooling operators for weakly labeled sound event detection

Massive MIMO with Spatially Correlated Rician Fading Channels

Neural Network Renormalization Group

Bridging the Gap Between Safety and Real-Time Performance in Receding-Horizon Trajectory Design for Mobile Robots

Quantum Image Processing and Its Application to Edge Detection: Theory and Experiment

The Tensor Networks Anthology: Simulation techniques for many-body quantum lattice systems

A Mean Field View of the Landscape of Two-Layers Neural Networks

Generative Modeling using the Sliced Wasserstein Distance

Computational Optimal Transport

Efficient Exploration via State Marginal Matching

The quantum Rabi model: solution and dynamics

Deep Neural Networks as Gaussian Processes

Gaussian Differential Privacy