Deep Learning · Generative Models

TitleAuthors
A Primal-Dual link between GANs and AutoencodersHisham Husain · Richard Nock · Robert Williamson
A Prior of a Googol Gaussians: a Tensor Ring Induced Prior for Generative ModelsMaxim Kuznetsov · Daniil Polykovskiy · Dmitry Vetrov · Alex Zhebrak
Adversarial Self-Defense for Cycle-Consistent GANsDina Bashkirova · Ben Usman · Kate Saenko
Controllable Text-to-Image GenerationBowen Li · Xiaojuan Qi · Thomas Lukasiewicz · Philip Torr
Dancing to MusicHsin-Ying Lee · Xiaodong Yang · Ming-Yu Liu · Ting-Chun Wang · Yu-Ding Lu · Ming-Hsuan Yang · Jan Kautz
DppNet: Approximating Determinantal Point Processes with Deep NetworksZelda Mariet · Yaniv Ovadia · Jasper Snoek
Efficient Graph Generation with Graph Recurrent Attention NetworksRenjie Liao · Yujia Li · Yang Song · Shenlong Wang · Will Hamilton · David Duvenaud · Raquel Urtasun · Richard Zemel
Explicit Disentanglement of Appearance and Perspective in Generative ModelsNicki Skafte · Søren Hauberg
Flow-based Image-to-Image Translation with Feature DisentanglementRuho Kondo · Keisuke Kawano · Satoshi Koide · Takuro Kutsuna
Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy ProtectionBingzhe Wu · Shiwan Zhao · Chaochao Chen · Haoyang Xu · Li Wang · Xiaolu Zhang · Guangyu Sun · Jun Zhou
Improved Precision and Recall Metric for Assessing Generative ModelsTuomas Kynkäänniemi · Tero Karras · Samuli Laine · Jaakko Lehtinen · Timo Aila
Knowledge Extraction with No Observable DataJaemin Yoo · Minyong Cho · Taebum Kim · U Kang
Learn, Imagine and Create: Text-to-Image Generation from Prior KnowledgeTingting Qiao · Jing Zhang · Duanqing Xu · Dacheng Tao
PasteGAN: A Semi-Parametric Method to Generate Image from Scene GraphYikang LI · Tao Ma · Yeqi Bai · Nan Duan · Sining Wei · Xiaogang Wang
Sequential Neural ProcessesGautam Singh · Jaesik Yoon · Youngsung Son · Sungjin Ahn
Unsupervised Keypoint Learning for Guiding Class-Conditional Video PredictionYunji Kim · Seonghyeon Nam · In Cho · Seon Joo Kim
Adaptive Density Estimation for Generative ModelsThomas Lucas · Konstantin Shmelkov · Karteek Alahari · Cordelia Schmid · Jakob Verbeek
Adversarial Fisher Vectors for Unsupervised Representation LearningJoshua Susskind · Shuangfei Zhai · Walter Talbott · Carlos Guestrin
Co-Generation with GANs using AIS based HMCTiantian Fang · Alexander Schwing
Compression with Flows via Local Bits-Back CodingJonathan Ho · Evan Lohn · Pieter Abbeel
Direct Optimization through \arg \max for Discrete Variational Auto-EncoderGuy Lorberbom · Tommi Jaakkola · Andreea Gane · Tamir Hazan
Fast and Provable ADMM for Learning with Generative PriorsFabian Latorre · Armin eftekhari · Volkan Cevher
Generative Modeling by Estimating Gradients of the Data DistributionYang Song · Stefano Ermon
HYPE: A Benchmark for Human eYe Perceptual Evaluation of Generative ModelsSharon Zhou · Mitchell Gordon · Ranjay Krishna · Austin Narcomey · Li Fei-Fei · Michael Bernstein
Implicit Generation and Modeling with Energy Based ModelsYilun Du · Igor Mordatch
Invertible Convolutional FlowMahdi Karami · Dale Schuurmans · Jascha Sohl-Dickstein · Laurent Dinh · Daniel Duckworth
Latent Ordinary Differential Equations for Irregularly-Sampled Time SeriesYulia Rubanova · Tian Qi Chen · David Duvenaud
MaCow: Masked Convolutional Generative FlowXuezhe Ma · Xiang Kong · Shanghang Zhang · Eduard Hovy
Mining GOLD Samples for Conditional GANsSangwoo Mo · Chiheon Kim · Sungwoong Kim · Minsu Cho · Jinwoo Shin
Learning Non-Convergent Non-Persistent Short-Run MCMC Toward Energy-Based ModelErik Nijkamp · Mitch Hill · Song-Chun Zhu · Ying Nian Wu
Residual Flows for Invertible Generative ModelingTian Qi Chen · Jens Behrmann · David Duvenaud · Joern-Henrik Jacobsen
Time-series Generative Adversarial NetworksJinsung Yoon · Daniel Jarrett · M Van Der Schaar
Twin Auxilary Classifiers GANMingming Gong · Yanwu Xu · Chunyuan Li · Kun Zhang · Kayhan Batmanghelich
Deep Generative Video CompressionSalvator Lombardo · JUN HAN · Christopher Schroers · Stephan Mandt
A Model to Search for Synthesizable MoleculesJohn Bradshaw · Brooks Paige · Matt Kusner · Marwin Segler · José Miguel Hernández-Lobato
BIVA: A Very Deep Hierarchy of Latent Variables for Generative ModelingLars Maaløe · Marco Fraccaro · Valentin Liévin · Ole Winther
Classification Accuracy Score for Conditional Generative ModelsSuman Ravuri · Oriol Vinyals
Discrete Flows: Invertible Generative Models of Discrete DataDustin Tran · Keyon Vafa · Kumar Agrawal · Laurent Dinh · Ben Poole
First Order Motion Model for Image AnimationAliaksandr Siarohin · Stéphane Lathuillère · Sergey Tulyakov · Elisa Ricci · Nicu Sebe
G2SAT: Learning to Generate SAT FormulasJiaxuan You · Haoze Wu · Clark Barrett · Raghuram Ramanujan · Jure Leskovec
Multi-objects Generation with Amortized Structural RegularizationTaufik Xu · Chongxuan LI · Jun Zhu · Bo Zhang
Neural Multisensory Scene InferenceJae Hyun Lim · Pedro O. Pinheiro · Negar Rostamzadeh · Chris Pal · Sungjin Ahn
Neural Spline FlowsConor Durkan · Artur Bekasov · Iain Murray · George Papamakarios
Progressive Augmentation of GANsDan Zhang · Anna Khoreva
Quantum Wasserstein Generative Adversarial NetworksShouvanik Chakrabarti · Huang Yiming · Tongyang Li · Soheil Feizi · Xiaodi Wu
Energy-Inspired Models: Learning with Sampler-Induced DistributionsJohn Lawson · George Tucker · Bo Dai · Rajesh Ranganath
Sequence Modeling with Unconstrained Generation OrderDmitrii Emelianenko · Elena Voita · Pavel Serdyukov
Symmetry-adapted generation of 3d point sets for the targeted discovery of moleculesNiklas Gebauer · Michael Gastegger · Kristof Schütt
Don't Blame the ELBO! A Linear VAE Perspective on Posterior CollapseJames Lucas · George Tucker · Roger Grosse · Mohammad Norouzi
Unsupervised Learning of Object Keypoints for Perception and ControlTejas Kulkarni · Ankush Gupta · Catalin Ionescu · Sebastian Borgeaud · Malcolm Reynolds · Andrew Zisserman · Volodymyr Mnih
A Domain Agnostic Measure for Monitoring and Evaluating GANsPaulina Grnarova · Kfir Y. Levy · Aurelien Lucchi · Nathanael Perraudin · Ian Goodfellow · Thomas Hofmann · Andreas Krause
Bias Correction of Learned Generative Models using Likelihood-Free Importance WeightingAditya Grover · Jiaming Song · Ashish Kapoor · Kenneth Tran · Alekh Agarwal · Eric Horvitz · Stefano Ermon
Copulas as High-Dimensional Generative Models: Vine Copula AutoencodersNatasa Tagasovska · Damien Ackerer · Thibault Vatter
Deep Random Splines for Point Process Intensity Estimation of Neural Population DataGabriel Loaiza-Ganem · Sean Perkins · Karen Schroeder · Mark Churchland · John Cunningham
Discrete Object Generation with Reversible Inductive ConstructionAri Seff · Wenda Zhou · Farhan Damani · Abigail Doyle · Ryan Adams
Generating Diverse High-Fidelity Images with VQ-VAE-2Ali Razavi · Aaron van den Oord · Oriol Vinyals
Generative Well-intentioned NetworksJustin Cosentino · Jun Zhu
Graph Normalizing FlowsJenny Liu · Aviral Kumar &mmiddot; Jimmy Ba · Jamie Kiros · Kevin Swersky
Icebreaker: Element-wise Efficient Information Acquisition with a Bayesian Deep Latent Gaussian ModelWenbo Gong · Sebastian Tschiatschek · Sebastian Nowozin · Richard E Turner · José Miguel Hernández-Lobato · Cheng Zhang
Integer Discrete Flows and Lossless CompressionEmiel Hoogeboom · Jorn Peters · Rianne van den Berg · Max Welling
Amortized Bethe Free Energy Minimization for Learning MRFsSam Wiseman · Yoon Kim
MintNet: Building Invertible Neural Networks with Masked ConvolutionsYang Song · Chenlin Meng · Stefano Ermon
NAOMI: Non-Autoregressive Multiresolution Sequence ImputationYukai Liu · Rose Yu · Stephan Zheng · Eric Zhan · Yisong Yue
ODE2VAE: Deep generative second order ODEs with Bayesian neural networksCagatay Yildiz · Markus Heinonen · Harri Lahdesmaki
Scalable Deep Generative Relational Model with High-Order Node DependenceXuhui Fan · Bin Li · Caoyuan Li · Scott SIsson · Ling Chen
Variational Mixture-of-Experts Autoencoders for Multi-Modal Deep Generative ModelsYuge Shi · Siddharth N · Brooks Paige · Philip Torr
Variational Temporal AbstractionTaesup Kim · Sungjin Ahn · Yoshua Bengio