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Machine learning with beauty and care.

Journal Club


The titles of the papers studied by our lab during our journal club are listed. Invited talks, or lab members presenting their own work are indicated by italics.

  • November 30th 2020. NeurIPS lightning round
  • November 23rd 2020. To understand deep learning, we need to understand kernel learning. Presented by Olga Vishnyakova
  • November 16th 2020. Multivariate random forests. Presented by Sonny Min
  • November 9th 2020. Statistical robustness of convolutional networks with a push-pull inhibition layer. Presented by Zubia Mansoor
  • November 2nd 2020. Statistical paradises and paradoxes in big data (I): Law of large populations, big data paradox, and the 2016 US presidential election. Presented by Winfield
  • October 26th 2020. Instance-level decision visualization of Random Forest models. Presented by Hannah Sutton
  • October 19th 2020. Manifold regression. Presented by Matthew Parker
  • September 24th 2020. Genotype compression with through finite-state entropy. Presented by Winfield Chen
  • September 17th 2020. treespace: Statistical exploration of landscapes of phylogenetic trees. Presented by Hannah Sutton
  • September 10th 2020. On-line random forests. Presented by Sonny Min
  • August 13th 2020. Extending N-mixtures: Auxiliary populations and large abundance models. Online invited talk by Matthew Parker
  • July 30th 2020. Bayesian inference with TensorFlow Probability. Online invited talk by Emily Fertig
  • July 23rd 2020. Text-Independent Speaker Recognition based on DNN embeddings. Online invited talk by Olga Vishnyakova
  • July 9th 2020. Fermat’s polygonal number theorem for repeated generalized polygonal numbers. Online invited talk by Muratzhan Kyranbay
  • June 25th 2020. Behaviour trees for AI: How they work. Presented by Wendy Wang
  • June 18th 2020. Human-level control through deep reinforcement learning. Presented by Sonny Min
  • June 11th 2020. MCMC with people. Presented by Zubia Mansoor
  • May 14th 2020. Bayesian estimation of three-dimensional chromosomal structure from single-cell Hi-C data. Part II. Presented by Winfield Chen
  • May 7th 2020. Genome-wide association studies in ancestrally diverse populations: Opportunities, methods, pitfalls, and recommendations. Presented by Pulindu Ratnasekera
  • April 30th 2020. Replica conditional SMC. Online invited talk Alex Shestopaloff
  • April 16th 2020. Inferring the Ancestry of Everyone. Presented by Payman Nickchi
  • April 2nd 2020. Bayesian estimation of three-dimensional chromosomal structure from single-cell Hi-C data. Part I. Presented by Lloyd Elliott
  • March 26th 2020. Stochastic geometry to generalize the Mondrian process. Presented by Shijia Wang
  • March 19th 2020. Kinship solutions for partially observed multiphenotype data. Presented by Lloyd Elliott
  • March 12th 2020. CART: Classification and Regression Trees. Presented by Hannah Sutton
  • March 5th 2020. Bayesian model averaging: A tutorial. Presented by Zubia Mansoor
  • February 13th 2020. Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study. Presented by Winfield Chen
  • January 30th 2020. The elements of statistical learning (Chapter 12). Presented by Shufei Ge
  • January 23rd. Memory (and time) efficient sequential Monte Carlo. Presented by Sonny Min
  • January 16th 2020. Cybernetics: Or Control and Communication in the Animal and the Machine. Presented by Lloyd Elliott
  • December 6th 2019. NeurIPS Lightning Round. Part II
  • November 29th 2019. NeurIPS Lightning Round. Part I
  • November 22. Split-plot design. Split-plot designs: What, why, and how. Presented by Sonny Min
  • November 15th 2019. Regression shrinkage and selection via the LASSO. Presented by Zubia Mansoor
  • November 8th 2019. Cannonical correlation forests. Presented by Shufei Ge
  • November 1st 2019. Asymmetric numeral systems. Presented by Winfield Chen
  • October 25th 2019. A mathematical theory of communication. Presented by Lloyd Elliott
  • October 18th 2019. AlexNet. Presented by Sonny Min
  • October 11th 2019. Random forests. Presented by Zubia Mansoor
  • October 4th 2019. Generalized random forests. Presented by Shufei Ge
  • September 13th 2019. The Mondrian kernel. Presented by Shijia Wang
  • June 12th 2019. Inferring the ancestry of everyone. Presented by Shijia Wang
  • June 5th 2019. GenPress: A novel dictionary based method to compress DNA data of various species. Presented by Winfield Chen
  • April 24th 2019. Interacting particle Markov chain Monte Carlo. Particle Gibbs for Bayesian additive regression trees. Presented by Shufei Ge
  • April 17th 2019. BART: Bayesian additive regression trees. Presented by Shufei Ge
  • March 27th 2019. Generalizing tree probability estimation via Bayesian networks. Presented by Shijia Wang
  • March 20th 2019. Modeling population structure under hierarchical Dirichlet processes. Presented by Shijia Wang
  • March 13th 2019. Crack STIT tessellations (Part II). Presented by Lloyd Elliott
  • February 27th 2019. Crack STIT tessellations (Part I). Presented by Shufei Ge
  • February 20th 2019. Screen and clean. Presented by Shijia Wang
  • February 13th 2019. Singleton variants dominate the genetic architecture of human gene expression. Presented by Lloyd Elliott
  • January 30th 2019. Geometry of STIT: Connection with Poisson hyperplanes. Presented by Shufei Ge
  • January 24th 2019. Gibbs flow for approximate transport with applications to Bayesian computation. Presented by Shijia Wang
  • January 16th 2019. Lack of group-to-individual generalizability is a threat to human subjects research. Presented by Lloyd Elliott
  • January 9th 2019. Mondrian forests: Efficient online random forests. Presented by Shufei Ge
  • January 4th 2019. Bayesian neural networks for selection of anticancer drug response genes. Presented by Shijia Wang