Bidirectional Inference Networks: A Class of Deep Bayesian Networks for Health Profiling
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Hao He | Tommi S. Jaakkola | Dina Katabi | Hao Wang | Mingmin Zhao | Chengzhi Mao | T. Jaakkola | Hao He | D. Katabi | Hao Wang | Chengzhi Mao | Mingmin Zhao
[1] J. Besag. Spatial Interaction and the Statistical Analysis of Lattice Systems , 1974 .
[2] C. Sherbourne,et al. The MOS 36-Item Short-Form Health Survey (SF-36) , 1992 .
[3] Ware J.E.Jr.,et al. THE MOS 36- ITEM SHORT FORM HEALTH SURVEY (SF- 36) CONCEPTUAL FRAMEWORK AND ITEM SELECTION , 1992 .
[4] C. McHorney,et al. The MOS 36‐Item Short‐Form Health Survey (SF‐36): II. Psychometric and Clinical Tests of Validity in Measuring Physical and Mental Health Constructs , 1993, Medical care.
[5] J. Samet,et al. The Sleep Heart Health Study: design, rationale, and methods. , 1997, Sleep.
[6] J. Larson. The MOS 36-Item Short form Health Survey , 1997, Evaluation & the health professions.
[7] Hugo Larochelle,et al. The Neural Autoregressive Distribution Estimator , 2011, AISTATS.
[8] Harry Joe,et al. Composite Likelihood Methods , 2012 .
[9] Hugo Larochelle,et al. RNADE: The real-valued neural autoregressive density-estimator , 2013, NIPS.
[10] T. Kadir,et al. Bayesian Networks for Clinical Decision Support in Lung Cancer Care , 2013, PloS one.
[11] Max Welling,et al. Auto-Encoding Variational Bayes , 2013, ICLR.
[12] Christian Osendorfer,et al. Learning Stochastic Recurrent Networks , 2014, NIPS 2014.
[13] Joan Bruna,et al. Intriguing properties of neural networks , 2013, ICLR.
[14] Quoc V. Le,et al. Distributed Representations of Sentences and Documents , 2014, ICML.
[15] Yoshua Bengio,et al. A Recurrent Latent Variable Model for Sequential Data , 2015, NIPS.
[16] Dit-Yan Yeung,et al. Collaborative Deep Learning for Recommender Systems , 2014, KDD.
[17] Honglak Lee,et al. Learning Structured Output Representation using Deep Conditional Generative Models , 2015, NIPS.
[18] Uri Shalit,et al. Deep Kalman Filters , 2015, ArXiv.
[19] Hugo Larochelle,et al. MADE: Masked Autoencoder for Distribution Estimation , 2015, ICML.
[20] Alex Graves,et al. DRAW: A Recurrent Neural Network For Image Generation , 2015, ICML.
[21] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[22] Jonathon Shlens,et al. Explaining and Harnessing Adversarial Examples , 2014, ICLR.
[23] Hugo Larochelle,et al. Neural Autoregressive Distribution Estimation , 2016, J. Mach. Learn. Res..
[24] Leon A. Gatys,et al. Image Style Transfer Using Convolutional Neural Networks , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[25] Nicholas Jing Yuan,et al. Collaborative Knowledge Base Embedding for Recommender Systems , 2016, KDD.
[26] Ryan P. Adams,et al. Composing graphical models with neural networks for structured representations and fast inference , 2016, NIPS.
[27] Dit-Yan Yeung,et al. Towards Bayesian Deep Learning: A Framework and Some Existing Methods , 2016, IEEE Transactions on Knowledge and Data Engineering.
[28] Il Memming Park,et al. BLACK BOX VARIATIONAL INFERENCE FOR STATE SPACE MODELS , 2015, 1511.07367.
[29] Andrew McCallum,et al. Structured Prediction Energy Networks , 2015, ICML.
[30] Dit-Yan Yeung,et al. Natural-Parameter Networks: A Class of Probabilistic Neural Networks , 2016, NIPS.
[31] Ole Winther,et al. Sequential Neural Models with Stochastic Layers , 2016, NIPS.
[32] Dit-Yan Yeung,et al. Relational Deep Learning: A Deep Latent Variable Model for Link Prediction , 2017, AAAI.
[33] Andrew McCallum,et al. End-to-End Learning for Structured Prediction Energy Networks , 2017, ICML.
[34] Leon A. Gatys,et al. Controlling Perceptual Factors in Neural Style Transfer , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[35] Mohammad Emtiyaz Khan,et al. Variational Message Passing with Structured Inference Networks , 2018, ICLR.
[36] Hongyi Zhang,et al. mixup: Beyond Empirical Risk Minimization , 2017, ICLR.