| Machine Learning Estimation of Heterogeneous Treatment Effects with Instruments | Vasilis Syrgkanis · Victor Lei · Miruna Oprescu · Maggie Hei · Keith Battocchi · Greg Lewis |
| On Exact Computation with an Infinitely Wide Neural Net | Sanjeev Arora · Simon Du · Wei Hu · Zhiyuan Li · Russ Salakhutdinov · Ruosong Wang |
| List-decodable Linear Regression | Sushrut Karmalkar · Adam Klivans · Pravesh Kothari |
| Legendre Memory Units: Continuous-Time Representation in Recurrent Neural Networks | Aaron Voelker · Ivana Kajić · Chris Eliasmith |
| Identification of Conditional Causal Effects under Markov Equivalence | Amin Jaber · Jiji Zhang · Elias Bareinboim |
| Generalization Bounds of Stochastic Gradient Descent for Wide and Deep Neural Networks | Yuan Cao · Quanquan Gu |
| On the Hardness of Robust Classification | Pascale Gourdeau · Varun Kanade · Marta Kwiatkowska · James Worrell |
| Point-Voxel CNN for Efficient 3D Deep Learning | Zhijian Liu · Haotian Tang · Yujun Lin · Song Han |
| Likelihood-Free Overcomplete ICA and Applications In Causal Discovery | Chenwei DING · Mingming Gong · Kun Zhang · Dacheng Tao |
| Efficient and Accurate Estimation of Lipschitz Constants for Deep Neural Networks | Mahyar Fazlyab · Alexander Robey · Hamed Hassani · Manfred Morari · George Pappas |
| Adversarial Examples Are Not Bugs, They Are Features | Andrew Ilyas · Shibani Santurkar · Dimitris Tsipras · Logan Engstrom · Brandon Tran · Aleksander Madry |
| Neural Networks with Cheap Differential Operators | Tian Qi Chen · David Duvenaud |
| Perceiving the arrow of time in autoregressive motion | Kristof Meding · Dominik Janzing · Bernhard Schölkopf · Felix A. Wichmann |
| Towards Explaining the Regularization Effect of Initial Large Learning Rate in Training Neural Networks | Yuanzhi Li · Colin Wei · Tengyu Ma |
| Empirically Measuring Concentration: Fundamental Limits on Intrinsic Robustness | Saeed Mahloujifar · Xiao Zhang · Mohammad Mahmoody · David Evans |
| Sequential Neural Processes | Gautam Singh · Jaesik Yoon · Youngsung Son · Sungjin Ahn |
| Conditional Independence Testing using Generative Adversarial Networks | Alexis Bellot · Mihaela van der Schaar |
| Data-dependent Sample Complexity of Deep Neural Networks via Lipschitz Augmentation | Colin Wei · Tengyu Ma |
| Quantum Entropy Scoring for Fast Robust Mean Estimation and Improved Outlier Detection | Yihe Dong · Samuel Hopkins · Jerry Li |
| Deep Equilibrium Models | Shaojie Bai · J. Zico Kolter · Vladlen Koltun |
| Imitation Learning from Observations by Minimizing Inverse Dynamics Disagreement | Chao Yang · Xiaojian Ma · Wenbing Huang · Fuchun Sun · Huaping Liu · Junzhou Huang · Chuang Gan |
| Learning Hierarchical Priors in VAEs | Alexej Klushyn · Nutan Chen · Richard Kurle · Botond Cseke · Patrick van der Smagt |
| Asymmetric Valleys: Beyond Sharp and Flat Local Minima | Haowei He · Gao Huang · Yang Yuan |
| Scalable Global Optimization via Local Bayesian Optimization | David Eriksson · Michael Pearce · Jacob Gardner · Ryan Turner · Matthias Poloczek |
| Learning to Control Self-Assembling Morphologies: A Study of Generalization via Modularity | Deepak Pathak · Christopher Lu · Trevor Darrell · Phillip Isola · Alexei Efros |
| Implicit Generation and Modeling with Energy Based Models | Yilun Du · Igor Mordatch |
| Reducing the variance in online optimization by transporting past gradients | Sébastien Arnold · Pierre-Antoine Manzagol · Reza Babanezhad Harikandeh · Ioannis Mitliagkas · Nicolas Le Roux |
| Uncertainty on Asynchronous Time Event Prediction | Marin Biloš · Bertrand Charpentier · Stephan Günnemann |
| A Structured Prediction Approach for Generalization in Cooperative Multi-Agent Reinforcement Learning | Nicolas Carion · Nicolas Usunier · Gabriel Synnaeve · Alessandro Lazaric |
| Invertible Convolutional Flow | Mahdi Karami · Dale Schuurmans · Jascha Sohl-Dickstein · Laurent Dinh · Daniel Duckworth |
| Who is Afraid of Big Bad Minima? Analysis of gradient-flow in spiked matrix-tensor models | Stefano Sarao Mannelli · Giulio Biroli · Chiara Cammarota · Florent Krzakala · Lenka Zdeborová |
| Bayesian Optimization under Heavy-tailed Payoffs | Sayak Ray Chowdhury · Aditya Gopalan |
| Learning Compositional Neural Programs with Recursive Tree Search and Planning | Thomas PIERROT · Guillaume Ligner · Scott Reed · Olivier Sigaud · Nicolas Perrin · Alexandre Laterre · David Kas · Karim Beguir · Nando de Freitas |
| Residual Flows for Invertible Generative Modeling | Tian Qi Chen · Jens Behrmann · David Duvenaud · Joern-Henrik Jacobsen |
| Fast and Provable ADMM for Learning with Generative Priors | Fabian Latorre · Armin eftekhari · Volkan Cevher |
| Variational Bayesian Optimal Experimental Design | Adam Foster · Martin Jankowiak · Elias Bingham · Paul Horsfall · Yee Whye Teh · Thomas Rainforth · Noah Goodman |
| Guided Meta-Policy Search | Russell Mendonca · Abhishek Gupta · Rosen Kralev · Pieter Abbeel · Sergey Levine · Chelsea Finn |
| Dual Variational Generation for Low Shot Heterogeneous Face Recognition | Chaoyou Fu · Xiang Wu · Yibo Hu · Huaibo Huang · Ran He |
| Complexity of Highly Parallel Non-Smooth Convex Optimization | Sebastien Bubeck · Qijia Jiang · Yin-Tat Lee · Yuanzhi Li · Aaron Sidford |
| Implicit Posterior Variational Inference for Deep Gaussian Processes | Haibin YU · Yizhou Chen · Bryan Kian Hsiang Low · Patrick Jaillet · Zhongxiang Dai |
| Better Exploration with Optimistic Actor Critic | Kamil Ciosek · Quan Vuong · Robert Loftin · Katja Hofmann |
| Adaptive Density Estimation for Generative Models | Thomas Lucas · Konstantin Shmelkov · Karteek Alahari · Cordelia Schmid · Jakob Verbeek |
| SySCD: A System-Aware Parallel Coordinate Descent Algorithm | Nikolas Ioannou · Celestine Mendler-Dünner · Thomas Parnell |
| Divide and Couple: Using Monte Carlo Variational Objectives for Posterior Approximation | Justin Domke · Daniel Sheldon |
| Robust exploration in linear quadratic reinforcement learning | Jack Umenberger · Mina Ferizbegovic · Thomas Schön · Håkan Hjalmarsson |
| Twin Auxilary Classifiers GAN | Mingming Gong · Yanwu Xu · Chunyuan Li · Kun Zhang · Kayhan Batmanghelich |
| Learning Positive Functions with Pseudo Mirror Descent | Yingxiang Yang · Haoxiang Wang · Negar Kiyavash · Niao He |
| The Randomized Midpoint Method for Log-Concave Sampling | Ruoqi Shen · Yin Tat Lee |
| Tight Regret Bounds for Model-Based Reinforcement Learning with Greedy Policies | Yonathan Efroni · Nadav Merlis · Mohammad Ghavamzadeh · Shie Mannor |
| Adversarial Fisher Vectors for Unsupervised Representation Learning | Joshua Susskind · Shuangfei Zhai · Walter Talbott · Carlos Guestrin |
| UniXGrad: A Universal, Adaptive Algorithm with Optimal Guarantees for Constrained Optimization | Ali Kavis · Kfir Y. Levy · Francis Bach · Volkan Cevher |
| Poisson-Minibatching for Gibbs Sampling with Convergence Rate Guarantees | Ruqi Zhang · Christopher De Sa |
| Hindsight Credit Assignment | Anna Harutyunyan · Will Dabney · Thomas Mesnard · Mohammad Gheshlaghi Azar · Bilal Piot · Nicolas Heess · Hado van Hasselt · Gregory Wayne · Satinder Singh · Doina Precup · Remi Munos |
| Emergence of Object Segmentation in Perturbed Generative Models | Adam Bielski · Paolo Favaro |
| Sinkhorn Barycenters with Free Support via Frank-Wolfe Algorithm | Giulia Luise · Saverio Salzo · Massimiliano Pontil · Carlo Ciliberto |
| Stochastic Proximal Langevin Algorithm: Potential Splitting and Nonasymptotic Rates | Adil SALIM · Dmitry Koralev · Peter Richtarik |
| Weight Agnostic Neural Networks | Adam Gaier · David Ha |
| Compression with Flows via Local Bits-Back Coding | Jonathan Ho · Evan Lohn · Pieter Abbeel |
| Learning dynamic polynomial proofs | Alhussein Fawzi · Mateusz Malinowski · Hamza Fawzi · Omar Fawzi |
| Stochastic Runge-Kutta Accelerates Langevin Monte Carlo and Beyond | Xuechen Li · Yi Wu · Lester Mackey · Murat Erdogdu |
| Calibration tests in multi-class classification: A unifying framework | David Widmann · Fredrik Lindsten · Dave Zachariah |
| A Condition Number for Joint Optimization of Cycle-Consistent Networks | Leonidas J Guibas · Qixing Huang · Zhenxiao Liang |
| DualDICE: Behavior-Agnostic Estimation of Discounted Stationary Distribution Corrections | Ofir Nachum · Yinlam Chow · Bo Dai · Lihong Li |
| Sparse Logistic Regression Learns All Discrete Pairwise Graphical Models | Shanshan Wu · Sujay Sanghavi · Alexandros Dimakis |
| Verified Uncertainty Calibration | Ananya Kumar · Percy Liang · Tengyu Ma |
| Cascade RPN: Delving into High-Quality Region Proposal Network with Adaptive Convolution | Thang Vu · Hyunjun Jang · Trung X. Pham · Chang Yoo |
| VIREL: A Variational Inference Framework for Reinforcement Learning | Matthew Fellows · Anuj Mahajan · Tim G. J. Rudner · Shimon Whiteson |
| Fast Convergence of Belief Propagation to Global Optima: Beyond Correlation Decay | Frederic Koehler |
| Fast structure learning with modular regularization | Greg Ver Steeg · Hrayr Harutyunyan · Daniel Moyer · Aram Galstyan |
| Probabilistic Watershed: Sampling all spanning forests for seeded segmentation and semi-supervised learning | Enrique Fita Sanmartin · Sebastian Damrich · Fred Hamprecht |
| Unsupervised Curricula for Visual Meta-Reinforcement Learning | Allan Jabri · Kyle Hsu · Abhishek Gupta · Ben Eysenbach · Sergey Levine · Chelsea Finn |
| Smoothing Structured Decomposable Circuits | Andy Shih · Guy Van den Broeck · Paul Beame · Antoine Amarilli |
| Principal Component Projection and Regression in Nearly Linear Time through Asymmetric SVRG | Yujia Jin · Aaron Sidford |
| DM2C: Deep Mixed-Modal Clustering | Yangbangyan Jiang · Qianqian Xu · Zhiyong Yang · Xiaochun Cao · Qingming Huang |
| Policy Continuation with Hindsight Inverse Dynamics | Hao Sun · Zhizhong Li · Xiaotong Liu · Bolei Zhou · Dahua Lin |
| Counting the Optimal Solutions in Graphical Models | Radu Marinescu · Rina Dechter |
| PIDForest: Anomaly Detection via Partial Identification | Parikshit Gopalan · Vatsal Sharan · Udi Wieder |
| Learning Object Bounding Boxes for 3D Instance Segmentation on Point Clouds | Bo Yang · Jianan Wang · Ronald Clark · Qingyong Hu · Sen Wang · Andrew Markham · Niki Trigoni |
| Learning Reward Machines for Partially Observable Reinforcement Learning | Rodrigo Toro Icarte · Ethan Waldie · Toryn Klassen · Rick Valenzano · Margarita Castro · Sheila McIlraith |
| Combining Generative and Discriminative Models for Hybrid Inference | Victor Garcia Satorras · Max Welling · Zeynep Akata |
| Fast and Flexible Multi-Task Classification using Conditional Neural Adaptive Processes | James Requeima · Jonathan Gordon · John Bronskill · Sebastian Nowozin · Richard Turner |
| Time/Accuracy Tradeoffs for Learning a ReLU with respect to Gaussian Marginals | Surbhi Goel · Sushrut Karmalkar · Adam Klivans |
| Are sample means in multi-armed bandits positively or negatively biased? | Jaehyeok Shin · Aaditya Ramdas · Alessandro Rinaldo |
| Finding Friend and Foe in Multi-Agent Games | Jack Serrino · Max Kleiman-Weiner · David Parkes · Josh Tenenbaum |
| Multimodal Model-Agnostic Meta-Learning via Task-Aware Modulation | Risto Vuorio · Shao-Hua Sun · Hexiang Hu · Joseph Lim |
| Limitations of Lazy Training of Two-layers Neural Network | Song Mei · Theodor Misiakiewicz · Behrooz Ghorbani · Andrea Montanari |
| SIC-MMAB: Synchronisation Involves Communication in Multiplayer Multi-Armed Bandits | Etienne Boursier · Vianney Perchet |
| Efficient Regret Minimization Algorithm for Extensive-Form Correlated Equilibrium | Gabriele Farina · Chun Kai Ling · Fei Fang · Tuomas Sandholm |
| Efficient Meta Learning via Minibatch Proximal Update | Pan Zhou · Xiaotong Yuan · Huan Xu · Shuicheng Yan · Jiashi Feng |
| Generalization Bounds for Neural Networks via Approximate Description Length | Amit Daniely · Elad Granot |
| Recovering Bandits | Ciara Pike-Burke · Steffen Grunewalder |
| Poincaré Recurrence, Cycles and Spurious Equilibria in Gradient-Descent-Ascent for Non-Convex Non-Concave Zero-Sum Games | Emmanouil-Vasileios Vlatakis-Gkaragkounis · Lampros Flokas · Georgios Piliouras |
| Reconciling meta-learning and continual learning with online mixtures of tasks | Ghassen Jerfel · Erin Grant · Tom Griffiths · Katherine Heller |
| Small ReLU networks are powerful memorizers: a tight analysis of memorization capacity | Chulhee Yun · Suvrit Sra · Ali Jadbabaie |
| Model Selection for Contextual Bandits | Dylan Foster · Akshay Krishnamurthy · Haipeng Luo |
| Multiagent Evaluation under Incomplete Information | Mark Rowland · Shayegan Omidshafiei · Karl Tuyls · Julien Perolat · Michal Valko · Georgios Piliouras · Remi Munos |
| Learning by Abstraction: The Neural State Machine | Drew Hudson · Christopher Manning |
| Cold Case: The Lost MNIST Digits | Chhavi Yadav · Leon Bottou |
| Beyond Online Balanced Descent: An Optimal Algorithm for Smoothed Online Optimization | Gautam Goel · Yiheng Lin · Haoyuan Sun · Adam Wierman |
| Graph-based Discriminators: Sample Complexity and Expressiveness | Roi Livni · Yishay Mansour |
| Heterogeneous Graph Learning for Visual Commonsense Reasoning | Weijiang Yu · Jingwen Zhou · Weihao Yu · Xiaodan Liang · Nong Xiao |
| An adaptive nearest neighbor rule for classification | Akshay Balsubramani · Sanjoy Dasgupta · yoav Freund · Shay Moran |
| Learning in Generalized Linear Contextual Bandits with Stochastic Delays | Zhengyuan Zhou · Renyuan Xu · Jose Blanchet |
| Nearly Tight Bounds for Robust Proper Learning of Halfspaces with a Margin | Ilias Diakonikolas · Daniel Kane · Pasin Manurangsi |
| Self-Critical Reasoning for Robust Visual Question Answering | Jialin Wu · Raymond Mooney |
| Multilabel reductions: what is my loss optimising? | Aditya Menon · Ankit Singh Rawat · Sashank Reddi · Sanjiv Kumar |
| Optimal Stochastic and Online Learning with Individual Iterates | Yunwen Lei · Peng Yang · Ke Tang · Ding-Xuan Zhou |
| McDiarmid-Type Inequalities for Graph-Dependent Variables and Stability Bounds | Rui (Ray) Zhang · Xingwu Liu · Yuyi Wang · Liwei Wang |
| SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems | Alex Wang · Yada Pruksachatkun · Nikita Nangia · Amanpreet Singh · Julian Michael · Felix Hill · Omer Levy · Samuel Bowman |
| Optimal Sparse Decision Trees | Xiyang Hu · Cynthia Rudin · Margo Seltzer |
| Online Learning via the Differential Privacy Lens | Jacob Abernethy · Young Hun Jung · Chansoo Lee · Audra McMillan · Ambuj Tewari |
| The Broad Optimality of Profile Maximum Likelihood | Yi Hao · Alon Orlitsky |
| Implicit Regularization in Deep Matrix Factorization | Sanjeev Arora · Nadav Cohen · Wei Hu · Yuping Luo |
| Learning Perceptual Inference by Contrasting | Chi Zhang · Baoxiong Jia · Feng Gao · Yixin Zhu · HongJing Lu · Song-Chun Zhu |
| Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers | Hadi Salman · Jerry Li · Ilya Razenshteyn · Pengchuan Zhang · Huan Zhang · Sebastien Bubeck · Greg Yang |
| Modeling Conceptual Understanding in Image Reference Games | Rodolfo Corona Rodriguez · Stephan Alaniz · Zeynep Akata |
| SGD on Neural Networks Learns Functions of Increasing Complexity | Dimitris Kalimeris · Gal Kaplun · Preetum Nakkiran · Benjamin Edelman · Tristan Yang · Boaz Barak · Haofeng Zhang |
| Universality and individuality in neural dynamics across large populations of recurrent networks | Niru Maheswaranathan · Alex Williams · Matthew Golub · Surya Ganguli · David Sussillo |
| Adversarial Music: Real world Audio Adversary against Wake-word Detection System | Juncheng Li · Shuhui Qu · Xinjian Li · Joseph Szurley · J. Zico Kolter · Florian Metze |
| This Looks Like That: Deep Learning for Interpretable Image Recognition | Chaofan Chen · Oscar Li · Daniel Tao · Alina Barnett · Cynthia Rudin · Jonathan K Su |
| When does label smoothing help? | Rafael Müller · Simon Kornblith · Geoffrey E Hinton |
| Better Transfer Learning with Inferred Successor Maps | Tamas Madarasz · Tim Behrens |
| Convergence of Adversarial Training in Overparametrized Neural Networks | Ruiqi Gao · Tianle Cai · Haochuan Li · Cho-Jui Hsieh · Liwei Wang · Jason Lee |
| Assessing Social and Intersectional Biases in Contextualized Word Representations | Yi Chern Tan · L. Elisa Celis |
| Splitting Steepest Descent for Growing Neural Architectures | Lemeng Wu · Dilin Wang · Qiang Liu |
| A unified theory for the origin of grid cells through the lens of pattern formation | Ben Sorscher · Gabriel Mel · Surya Ganguli · Samuel Ocko |
| Adversarial Training and Robustness for Multiple Perturbations | Florian Tramer · Dan Boneh |
| Paradoxes in Fair Machine Learning | Paul Goelz · Anson Kahng · Ariel Procaccia |
| Positional Normalization | Boyi Li · Felix Wu · Kilian Weinberger · Serge Belongie |
| Infra-slow brain dynamics as a marker for cognitive function and decline | Shagun Ajmera Shyam Sunder Ajmera · Shreya Rajagopal · Razi Rehman · Devarajan Sridharan |
| Zero-shot Knowledge Transfer via Adversarial Belief Matching | Paul Micaelli · Amos Storkey |
| Multi-Criteria Dimensionality Reduction with Applications to Fairness | Uthaipon Tantipongpipat · Samira Samadi · Mohit Singh · Jamie Morgenstern · Santosh Vempala |
| Asymptotic Guarantees for Learning Generative Models with the Sliced-Wasserstein Distance | Kimia Nadjahi · Alain Durmus · Umut Simsekli · Roland Badeau |
| Ask not what AI can do, but what AI should do: Towards a framework of task delegability | Brian Lubars · Chenhao Tan |
| On the Downstream Performance of Compressed Word Embeddings | Avner May · Jian Zhang · Tri Dao · Christopher Ré |
| A Nonconvex Approach for Exact and Efficient Multichannel Sparse Blind Deconvolution | Qing Qu · Xiao Li · Zhihui Zhu |
| Theoretical Analysis of Adversarial Learning: A Minimax Approach | Zhuozhuo Tu · Jingwei Zhang · Dacheng Tao |
| Making AI Forget You: Data Deletion in Machine Learning | Antonio Ginart · Melody Guan · Gregory Valiant · James Zou |
| CPM-Nets: Cross Partial Multi-View Networks | Changqing Zhang · Zongbo Han · yajie cui · Huazhu Fu · Joey Tianyi Zhou · Qinghua Hu |
| Efficiently Learning Fourier Sparse Set Functions | Andisheh Amrollahi · Amir Zandieh · Michael Kapralov · Andreas Krause |
| Statistical bounds for entropic optimal transport: sample complexity and the central limit theorem | Gonzalo Mena · Jonathan Niles-Weed |
| On Testing for Biases in Peer Review | Ivan Stelmakh · Nihar Shah · Aarti Singh |
| Numerically Accurate Hyperbolic Embeddings Using Tiling-Based Models | Tao Yu · Christopher De Sa |
| Generalization Error Analysis of Quantized Compressive Learning | Xiaoyun Li · Ping Li |
| Differentiable Ranking and Sorting using Optimal Transport | Marco Cuturi · Olivier Teboul · Jean-Philippe Vert |
| A Step Toward Quantifying Independently Reproducible Machine Learning Research | Edward Raff |
| Large Memory Layers with Product Keys | Guillaume Lample · Alexandre Sablayrolles · Marc'Aurelio Ranzato · Ludovic Denoyer · Herve Jegou |
| Surfing: Iterative Optimization Over Incrementally Trained Deep Networks | Ganlin Song · Zhou Fan · John Lafferty |
| KerGM: Kernelized Graph Matching | Zhen Zhang · Yijian Xiang · Lingfei Wu · Bing Xue · Arye Nehorai |
| Private Learning Implies Online Learning: An Efficient Reduction | Alon Gonen · Elad Hazan · Shay Moran |
| Cross-lingual Language Model Pretraining | Alexis CONNEAU · Guillaume Lample |
| Quadratic Video Interpolation | Xiangyu Xu · Li Siyao · Wenxiu Sun · Qian Yin · Ming-Hsuan Yang |
| Wasserstein Weisfeiler-Lehman Graph Kernels | Matteo Togninalli · Elisabetta Ghisu · Felipe Llinares-López · Bastian Rieck · Karsten Borgwardt |
| Private Stochastic Convex Optimization with Optimal Rates | Raef Bassily · Vitaly Feldman · Kunal Talwar · Abhradeep Guha Thakurta |
| N-Gram Graph: Simple Unsupervised Representation for Graphs, with Applications to Molecules | Shengchao Liu · Mehmet F Demirel · Yingyu Liang |
| Training Image Estimators without Image Ground Truth | Zhihao Xia · Ayan Chakrabarti |
| Regularization Matters: Generalization and Optimization of Neural Nets v.s. their Induced Kernel | Colin Wei · Jason Lee · Qiang Liu · Tengyu Ma |
| Practical Differentially Private Top-k Selection with Pay-what-you-get Composition | David Durfee · Ryan Rogers |
| Evaluating Protein Transfer Learning with TAPE | Roshan Rao · Nicholas Bhattacharya · Neil Thomas · Yan Duan · Peter Chen · John Canny · Pieter Abbeel · Yun Song |
| STREETS: A Novel Camera Network Dataset for Traffic Flow | Corey Snyder · Minh Do |
| Comparing distributions: $\ell_1$ geometry improves kernel two-sample testing | meyer scetbon · Gael Varoquaux |
| Differentially Private Markov Chain Monte Carlo | Mikko Heikkilä · Joonas Jälkö · Onur Dikmen · Antti Honkela |
| Cormorant: Covariant Molecular Neural Networks | Brandon Anderson · Truong Son Hy · Risi Kondor |
| Reflection Separation using a Pair of Unpolarized and Polarized Images | Youwei Lyu · Zhaopeng Cui · Si Li · Marc Pollefeys · Boxin Shi |