Spring 2017

When: May 11, 2017 2-4pm
Where: Jerome Greene Science Building - 3rd Floor Conf. Room
Presenter: Scott
Scribe: Yixin

Rao, Vinayak, Ryan P. Adams, and David D. Dunson. “Bayesian inference for Matérn repulsive processes.” Journal of the Royal Statistical Society: Series B (Statistical Methodology) 79.3 (2017): 877-897. link


When: April 27, 2017 2-4pm
Where: Jerome Greene Science Building - 3rd Floor Conf. Room
Presenter: Dar
Scribe: Andrew

Wibisono, Andre, Ashia C. Wilson, and Michael I. Jordan. “A Variational Perspective on Accelerated Methods in Optimization.” arXiv preprint arXiv:1603.04245 (2016). link

Mohamed, Shakir, and Balaji Lakshminarayanan. “Learning in Implicit Generative Models.” arXiv preprint arXiv:1610.03483 (2016). link


When: April 13, 2017 2-4pm
Where: Jerome Greene Science Building - 3rd Floor Conf. Room
Presenter: Yixin
Scribe: Liping

Arora, Sanjeev, et al. “Generalization and Equilibrium in Generative Adversarial Nets (GANs).” arXiv preprint arXiv:1703.00573 (2017). link

Gulrajani, Ishaan, et al. “Improved Training of Wasserstein GANs.” arXiv preprint arXiv:1704.00028 (2017). link


When: April 6, 2017 2-4pm
Where: Jerome Greene Science Building - 3rd Floor Conf. Room
Presenter: Peter
Scribe: Ian

Makhzani, Alireza, et al. “Adversarial autoencoders.” arXiv preprint arXiv:1511.05644 (2015). link

Burda, Yuri, Roger Grosse, and Ruslan Salakhutdinov. “Importance weighted autoencoders.” arXiv preprint arXiv:1509.00519 (2015). link


When: March 30, 2017 2-4pm
Where: Jerome Greene Science Building - 3rd Floor Conf. Room
Presenter: Gabriel
Scribe: Francois

van den Oord, Aaron, Nal Kalchbrenner, and Koray Kavukcuoglu. “Pixel Recurrent Neural Networks.” Proceedings of The 33rd International Conference on Machine Learning. 2016. link

Dinh, Laurent, Jascha Sohl-Dickstein, and Samy Bengio. “Density estimation using Real NVP.” To appear at The 5th International Conference on Learning Representations. (2017). link


When: March 23, 2017 2-4pm
Where: Jerome Greene Science Building - 3rd Floor Conf. Room
Presenter: Jalaj
Scribe: Tim

Bojarski, et al. “Structured adaptive and random spinners for fast machine learning computations.” To appear in AISTATS (2017). link

Wang, et. al. “Bayesian Optimization in a Billion Dimensions via Random Embeddings. link


When: March 9, 2017 2-4pm
Where: Jerome Greene Science Building - 3rd Floor Conf. Room
Presenter: Christian Naesseth
Scribe: Johannes Friedrich

Y. Ma, T. Chen, and E.B. Fox, “A Complete Recipe for Stochastic Gradient MCMC,” Neural Information Processing Systems (NIPS) (2015). link

Lu, Xiaoyu, et al. “Relativistic Monte Carlo.” To appear in AISTATS (2017). link


When: March 2, 2017 2-4pm
Where: Jerome Greene Science Building - 3rd Floor Conf. Room
Presenter: Robin Winstanley
Scribe: Dar Gilboa

Tamar, Aviv, Sergey Levine, and Pieter Abbeel. “Value Iteration Networks.” NIPS (2016). link

Finn, Chelsea, Ian Goodfellow, and Sergey Levine. “Unsupervised Learning for Physical Interaction through Video Prediction.” NIPS (2016). link


When: February 23, 2017 2-4pm
Where: Jerome Greene Science Building - 3rd Floor Conf. Room
Presenter: Ruoxi Sun
Scribe: Robin Winstanley

Arjovsky, Martin, Soumith Chintala, and Léon Bottou. “Wasserstein GAN.” arXiv preprint arXiv:1701.07875 (2017). link

Mescheder, Lars, Sebastian Nowozin, and Andreas Geiger. “Adversarial Variational Bayes: Unifying Variational Autoencoders and Generative Adversarial Networks.” arXiv preprint arXiv:1701.04722 (2017). link


When: February 16, 2017 2-4pm
Where: Jerome Greene Science Building - 3rd Floor Conf. Room
Presenter: Andrew Davison
Scribe: Gabriel Laoiza

Kakade, Sham, et al. “Prediction with a Short Memory.” arXiv preprint arXiv:1612.02526 (2016). link


When: February 9, 2017 2-4pm
Where: Jerome Greene Science Building - 5th Floor Conf. Room
Presenter: Yuanjun Gao
Scribe: Peter

Rezende, Danilo Jimenez, et al. “One-Shot Generalization in Deep Generative Models.” arXiv preprint arXiv:1603.05106 (2016). link

Lake, Brenden M., Ruslan Salakhutdinov, and Joshua B. Tenenbaum. “Human-level concept learning through probabilistic program induction.” Science 350.6266 (2015): 1332-1338. link


When: February 2, 2017 2-4pm
Where: Jerome Greene Science Building - 5th Floor Conf. Room
Presenter: Maja Rudolph
Scribe: Scott Linderman

Khan, Mohammad E., et al. “Kullback-Leibler proximal variational inference.” Advances in Neural Information Processing Systems. 2015. link

Khan, Mohammad E., et al. “Faster stochastic variational inference using Proximal-Gradient methods with general divergence functions.” arXiv preprint arXiv:1511.00146 (2015). link


When: January 26, 2017 2-4pm
Where: Jerome Greene Science Building - 5th Floor Conf. Room
Presenter: Shizhe Chen
Scribe: Gonzalo Mena

Jang, Eric et al. “Categorical Reparameterization with Gumbel-softmax.” (2016) link

Maddison, Chris J et al. “The concrete distribution: a continuous relaxation of discrete random variables.” (2016) link

Kusner, Matt J. and José Miguel Hernández-Lobato. “GANs for Sequences of Discrete Elements with the Gumbel-softmax Distribution.” (2016) link

Also of note: Tokui, Seiya. “Reparameterization trick for discrete variables.” arXiv preprint arXiv:1611.01239 (2016). link


Fall 2016

When: December 15, 2016 2-4pm
Where: 1025 SSW
Presenter: Everyone
Scribe: No one

A review of NIPS papers. Please check the NIPS pre-proceedings and come prepared to discuss a few of your favorites!


When: December 1, 2016 2-4pm
Where: 1025 SSW
Presenter: Adji Dieng
Scribe: Andrew Davison

Johnson, Matthew J., et al. “Composing graphical models with neural networks for structured representations and fast inference.” Advances in Neural Information Processing Systems (2016). link

Gao, Yuanjun, et al. “Linear dynamical neural population models through nonlinear embeddings.” Advances in Neural Information Processing Systems (2016). link

(optional) Krishnan, Rahul G., Uri Shalit, and David Sontag. “Deep Kalman Filters.”arXiv preprint arXiv:1511.05121 (2015). link


When: November 17, 2016 2-4pm
Where: 1025 SSW
Presenter: Gabriel Laoiza
Scribe: Gamal Elsayed

Uria, Benigno, et al. “Neural Autoregressive Distribution Estimation.” arXiv preprint arXiv:1605.02226 (2016). link

Germain, Mathieu, et al. “MADE: masked autoencoder for distribution estimation.” International Conference on Machine Learning. 2015. link


When: November 10, 2016 2-4pm
Where: 1025 SSW
Presenter: Yixin Wang
Scribe: Si Kai Lee

Huang, Gao, et al. “Deep networks with stochastic depth.” arXiv preprint arXiv:1603.09382 (2016). link

Gal, Yarin, and Zoubin Ghahramani. “Dropout as a Bayesian approximation: Representing model uncertainty in deep learning.” arXiv preprint arXiv:1506.02142 (2015). link


When: November 3, 2016 2-4pm
Where: 1025 SSW
Presenter: Dar Gilboa
Scribe: Kriste Krstovski

Advani, Madhu, and Surya Ganguli. “Statistical Mechanics of Optimal Convex Inference in High Dimensions.” Physical Review X 6.3_ (2016): 031034. link


When: October 27, 2016 2-4pm
Where: 1025 SSW
Presenter: Francois Fagan
Scribe: Keyon Vafa

Kawaguchi, Kenji. “Deep Learning without Poor Local Minima.” To appear in Neural Information Processing Systems (NIPS) (2016). link

Mei, Song, Yu Bai, and Andrea Montanari. “The Landscape of Empirical Risk for Non-convex Losses.” arXiv preprint arXiv:1607.06534 (2016). link


When: October 20, 2016 2-4pm
Where: 1025 SSW
Presenter: Christian Naesseth
Scribe: Ghazal Fazelnia

Polloc, Murray et al. “The Scalable Langevin Exact Algorithm: Bayesian Inference for Big Data” arXiv preprint arXiv:1609.03436 (2016). link


When: October 13, 2016 2-4pm
Where: 1025 SSW
Presenter: Patrick Stinson
Scribe: Liping Liu

Gregor, Karol, et al. “DRAW: A recurrent neural network for image generation.” arXiv preprint arXiv:1502.04623 (2015). link

Xu, Kelvin, et al. “Show, attend and tell: Neural image caption generation with visual attention.” arXiv preprint arXiv:1502.03044 2.3 (2015). link

(optional) Eslami, S. M., et al. “Attend, Infer, Repeat: Fast Scene Understanding with Generative Models.” arXiv preprint arXiv:1603.08575 (2016). link

(optional) Mnih, Volodymyr, Nicolas Heess, and Alex Graves. “Recurrent models of visual attention.” Advances in Neural Information Processing Systems. 2014. link


When: October 6, 2016 2-4pm
Where: 1025 SSW
Presenter: Gonzalo Mena
Scribe: Dustin Tran

Goodfellow, Ian, et al. “Generative adversarial nets.” Neural Information Processing Systems (NIPS) (2014). link

Nowozin, Sebastian, Botond Cseke, and Ryota Tomioka. “f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization.” Neural Information Processing Systems (NIPS) (2016). link


When: September 29, 2016 2-4pm
Where: 1025 SSW
Presenter: Jalaj Bhandari
Scribe: Scott Linderman

Moreno, Alexander, et al. “Automatic Variational ABC.” arXiv preprint arXiv:1606.08549 (2016). link

Meeds, Edward, Robert Leenders, and Max Welling. “Hamiltonian ABC.” arXiv preprint arXiv:1503.01916 (2015). link

(optional) Meeds, Edward, and Max Welling. “GPS-ABC: Gaussian process surrogate approximate Bayesian computation.” arXiv preprint arXiv:1401.2838 (2014). link


When: September 22, 2016 2-4pm
Where: 1025 SSW
Presenter: Benjamin Bloem-Reddy
Scribe: Yuanjun Gao and Gabriel Loaiza Ganem

Rezende, Danilo Jimenez, and Shakir Mohamed. “Variational inference with normalizing flows.” arXiv preprint arXiv:1505.05770 (2015). link

Kingma, Diederik P., Tim Salimans, and Max Welling. “Improving Variational Inference with Inverse Autoregressive Flow.” arXiv preprint arXiv:1606.04934 (2016). link