📰 NeurIPS 2016 — accepted papers

NeurIPS 2016 is the 2016 edition of the Conference on Neural Information Processing Systems (NeurIPS). OpenAlex lists 177 papers of it; our library holds 1 with our summaries. Below: the most cited papers, every accepted paper, and ours with their topics, authors and institutions.

Most cited papers

By their OpenAlex citations; a paper with our summary links to its page here, the others to the original.

1. Improved deep metric learning with multi-class N-pair loss objective ↗Kihyuk Sohn1,240 citations
2. Deep ADMM-Net for compressive sensing MRI ↗Yan Yang, Jian Zhong Sun, Huibin Li et al.871 citations
3. Improved Variational Inference with Inverse Autoregressive Flow ↗Durk Kingma, Tim Salimans, Rafał Józefowicz et al.724 citations
4. Weight normalization: a simple reparameterization to accelerate training of deep neural networks ↗Tim Salimans, Diederik P. Kingma617 citations
5. Unifying count-based exploration and intrinsic motivation ↗Marc G. Bellemare, Sriram Srinivasan, Georg Ostrovski et al.612 citations
6. Diffusion-Convolutional Neural Networks ↗James R. Atwood, Don Towsley517 citations
7. Examples are not enough, learn to criticize! Criticism for Interpretability ↗Been Kim, Rajiv Khanna, Sanmi Koyejo499 citations
8. MS MARCO: A Human Generated MAchine Reading COmprehension Dataset. ↗Tri Gia Nguyen, Mir Rosenberg, Song Xia et al.419 citations
9. Dynamic Filter Networks ↗Xu Jia, Bert De Brabandere, Tinne Tuytelaars et al.315 citations
10. Temporal regularized matrix factorization for high-dimensional time series prediction ↗Hsiang‐Fu Yu, Nikhil Rao, Inderjit S. Dhillon306 citations

All accepted papers (177)

The most cited first; 1 with our summary link to their page here, the others to the original.

1. Improved deep metric learning with multi-class N-pair loss objective ↗Kihyuk Sohn1,240 citations
2. Deep ADMM-Net for compressive sensing MRI ↗Yan Yang, Jian Zhong Sun, Huibin Li et al.871 citations
3. Improved Variational Inference with Inverse Autoregressive Flow ↗Durk Kingma, Tim Salimans, Rafał Józefowicz et al.724 citations
4. Weight normalization: a simple reparameterization to accelerate training of deep neural networks ↗Tim Salimans, Diederik P. Kingma617 citations
5. Unifying count-based exploration and intrinsic motivation ↗Marc G. Bellemare, Sriram Srinivasan, Georg Ostrovski et al.612 citations
6. Diffusion-Convolutional Neural Networks ↗James R. Atwood, Don Towsley517 citations
7. Examples are not enough, learn to criticize! Criticism for Interpretability ↗Been Kim, Rajiv Khanna, Sanmi Koyejo499 citations
8. MS MARCO: A Human Generated MAchine Reading COmprehension Dataset. ↗Tri Gia Nguyen, Mir Rosenberg, Song Xia et al.419 citations
9. Dynamic Filter Networks ↗Xu Jia, Bert De Brabandere, Tinne Tuytelaars et al.315 citations
10. Temporal regularized matrix factorization for high-dimensional time series prediction ↗Hsiang‐Fu Yu, Nikhil Rao, Inderjit S. Dhillon306 citations
11. Residual networks behave like ensembles of relatively shallow networks ↗Andreas Veit, Michael J. Wilber, Serge Belongie300 citations
12. Regularization with stochastic transformations and perturbations for deep semi-supervised learning ↗Mehdi S. M. Sajjadi, Mehran Javanmardi, Tolga Taşdizen262 citations
13. Learning to poke by poking: experiential learning of intuitive physics ↗Pulkit Agrawal, Ashvin Nair, Pieter Abbeel et al.254 citations
14. Bayesian optimization with robust Bayesian neural networks ↗Jost Tobias Springenberg, Aaron Klein, Stefan Falkner et al.252 citations
15. Learning Transferrable Representations for Unsupervised Domain Adaptation ↗Ozan Şener, Hyun Oh Song, Ashutosh Saxena et al.226 citations
16. Supervised Learning with Tensor Networks ↗Edwin Miles Stoudenmire, David J. Schwab188 citations
17. Composing graphical models with neural networks for structured representations and fast inference ↗Matthew Johnson, David Duvenaud, Alexander B. Wiltschko et al.165 citations
18. 30th Conference on Neural Information Processing Systems (NIPS 2016) ↗George Papamakarios, Iain Murray164 citations
19. Learning feed-forward one-shot learners ↗Luca Bertinetto, João F. Henriques, Jack Valmadre et al.163 citations
20. CNNpack: packing convolutional neural networks in the frequency domain ↗Yunhe Wang, Chang Xu, Shan You et al.144 citations
21. Stochastic Gradient Methods for Distributionally Robust Optimization with f-divergences ↗Hongseok Namkoong, John C. Duchi131 citations
22. Combining Fully Convolutional and Recurrent Neural Networks for 3D Biomedical Image Segmentation ↗Jianxu Chen, Lin Yang, Yizhe Zhang et al.113 citations
23. Fairness in learning: classic and contextual bandits ↗Matthew Joseph, Michael J. Kearns, Jamie Morgenstern et al.95 citations
24. Proximal stochastic methods for nonsmooth nonconvex finite-sum optimization ↗Sashank Jakkam Reddi, Suvrit Sra, Barnabás Póczos et al.95 citations
25. Towards Conceptual Compression ↗Karol Gregor, Frederic Besse, Danilo Jimenez Rezende et al.95 citations

See all 177 papers in NeurIPS 2016 — accepted papers →

📄 Papers with our summary in our library (1)

The most cited first (OpenAlex citations plus our library's).

1. Convolutional Neural Networks on Graphs with Fast Localized Spectral FilteringConference on Neural Information Processing Systems (NeurIPS)Michael Defferrard, Xavier Bresson, Pierre Vandergheynst2016 · 1,801 citations

📚 Fields

🖥️Computer Science (1)

🧑‍🔬 Top authors

Authors with a page who published here most often: their works here, and the citations of those works.

🏛️ Top institutions

Institutions on the bylines of its works here, by the number of works.

🎓École Polytechnique Fédérale de LausanneLausanne · Switzerland1 work here

works and citations from OpenAlex and our library.

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