elliottlab

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.

• March 23rd 2023. Counterfactual evaluation and learning for seach recommendation and ad placement. Presented by Nadia Enhaili
• March 16th 2023. The cherry blossom prediction competition. Talks by Olga Vishnyakova and Sonny Min
• March 9th 2023. Statistics for COVID-19: Four applications. Talk by Lloyd Elliott
• March 2nd 2023. Predicting the prevalence of complex genetic diseases from individual genotype profiles using capsule networks. Presented by Olga Vishnyakova
• February 16th 2023. Spatial modeling of dyadic genetic relatedness data: Identifying factors associated with M. tuberculosis transmission in Moldova. Presented by Renny Doig
• February 9th 2023. Attention is all you need. Presented by Matthew Parker
• February 2nd 2023. Using genetic data to strengthen causal inference in observational research. Presented by Sonny Min
• December 13th 2022. Decoding the contents and strength of imagery before volitional engagement. Presented by Olga Vishnyakova
• December 6th 2022. Selection on functional longevity in a commercial population of dairy goats translates into significant differences in longevity in a common farm environment. Presented by Renny Doig
• November 29th 2022. Private and communication-efficient algorithms for entropy estimation. Presented by Nadia Enhaili
• November 22nd 2022. Time-varying covariates and semi-parametric regression in capture-recapture: An adaptive spline approach. Presented by Mathew Parker
• November 15th 2022. Quantifying structure in random forests. Talk by Hannah Sutton
• October 18th 2022. Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead. Presented by Sonny Min
• October 11th 2022. Statistical inference in a stochastic epidemic SEIR model with control intervention: Ebola as a case study. Presented by Renny Doig
• October 4th 2022. An integrated model decomposing the components of detection probability and abundance in unmarked populations. Presented by Matthew Parker
• September 12th 2022. Identification of aggravation-predicting gene polymorphisms in coronavirus disease 2019 patients using a candidate gene approach associated with multiple phase pathogenesis: A study in a Japanese city of 1 million people. Presented by Elika Garg
• August 15th 2022. Identification, inference and sensitivity analysis for causal mediation effects. Presented by Sonny Min
• August 8th 2022. Statistical tests for detecting variance effects in quantitative trait studies. Presented by Olga Vishnyakova
• July 25th 2022. CovidSIMVL: Transmission trees, superspreaders and contact tracing in agent based models of COVID-19. Presented by Renny Doig
• July 4th 2022. Forest floor visualizations of random forests. Presented by Hannah Sutton
• June 13th 2022. Genetics meets metabolomics: A genome-wide association study of metabolite profiles in human serum. Presented by Sonny Min
• June 6th 2022. Cross-trait assortative mating is widespread and inflates genetic correlation estimates. Presented by Olga Vishnyakova
• October 7th 2021. Low SARS-CoV-2 sero-prevalence based on anonymized residual sero-survey before and after first wave measures in British Columbia, Canada, March-May 2020. Presented by Sonny Min
• September 23rd 2021. Under-reporting of COVID-19 in the Northern Health Authority region of British Columbia. Online talk by Matthew Parker
• July 30th 2021. Long time frames to detect the impact of changing COVID-19 measures, Canada, March to July 2020. Online invited talk by Jessica Stockdale
• July 23rd 2021. Q-Learning with Online Trees. Presented by Sonny Min
• July 9th. Whole genome sequencing. Online talk by Elika Garg
• April 23rd 2021. Initial real world evidence for lower viral load of individuals who have been vaccinated by BNT162b2. Presented by Olga Vishnyakova
• April 16th 2021. CovidSIMVL: Transmission trees, superspreaders and contact tracing in agent based models of COVID-19. Presented by Hannah Sutton
• March 26th 2021. Estimating the extent of asymptomatic COVID-19 and its potential for community transmission: systematic review and meta-analysis. Presented by Matthew Parker
• March 19th 2021. Genetic mechanisms of critical illness in COVID-19. Presented by Elika Garg
• March 12th 2021. AlphaFold for COVID-19. Presented by Winfield Chen
• March 5th 2021. Common genetic variants identify targets for COVID-19 and individuals at high risk of severe disease. Presented by Lloyd Elliott
• February 26th 2021. A deep neural network model using random forests to extract feature representation for gene expression data classification. Presented by Hannah Sutton
• February 12th 2021. U-Net: Convolutional networks for biomedical image segmentation. Presented by Olga Vishnyakova
• February 5th 2021. Searching for activation functions. Presented by Matthew Parker
• January 29th 2021. Improved protein structure prediction using potentials from deep learning. Presented by Winfield Chen
• 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 Chen
• 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 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 talk by Olga Vishnyakova
• July 9th 2020. Fermat’s polygonal number theorem for repeated generalized polygonal numbers. Online 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 2020. 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 2019. 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