Unsupervised Representation Learning of Spatial Data via Multimodal Embedding. - Porter Jenkins; Ahmad Farag; Suhang Wang; Zhenhui Li (CIKM, 2019)

ClickGraph: Web Page Embedding using Clickstream Data for Multitask Learning. - Porter Jenkins (WWW (Companion Volume), 2019)

Learning Task-Specific City Region Partition. - Hongjian Wang 002; Porter Jenkins; Hua Wei 001; Fei Wu 007; Zhenhui Li (WWW, 2019)

Structured Paragraph Embeddings of Financial Earnings Calls. - Porter Jenkins (WWW (Companion Volume), 2020)

Natural Language Annotations for Search Engine Optimization. - Porter Jenkins; Jennifer Zhao; Heath Vinicombe; Anant Subramanian; Arun Prasad; Atillia Dobi; Eileen Li; Yunsong Guo (WWW, 2020)

A Probabilistic Simulator of Spatial Demand for Product Allocation. - Porter Jenkins; Hua Wei 001; J. Stockton Jenkins; Zhenhui Li (CoRR, 2020)

Neural Utility Functions. - Porter Jenkins; Ahmad Farag; J. Stockton Jenkins; Huaxiu Yao; Suhang Wang; Zhenhui Li (AAAI, 2021)

Probabilistic simulation of spatial demand for intelligent product allocation. - Porter Jenkins; Hua Wei 001; J. Stockton Jenkins; Zhenhui Li (GeoSim@SIGSPATIAL, 2021)

Knowledge-based Residual Learning. - Guanjie Zheng; Chang Liu 021; Hua Wei 001; Porter Jenkins; Chacha Chen; Tao Wen 006; Zhenhui Li (IJCAI, 2021)

Overview of the 1st Workshop on City Brain Research. - Guanjie Zheng; Porter Jenkins; Yanyan Xu 002; Dongyao Chen (KDD, 2021)

Bayesian Model-Based Offline Reinforcement Learning for Product Allocation. - Porter Jenkins; Hua Wei 001; J. Stockton Jenkins; Zhenhui Li (AAAI, 2022)

CountNet3D: A 3D Computer Vision Approach to Infer Counts of Occluded Objects. - Porter Jenkins; Kyle Armstrong; Stephen Nelson; Siddhesh Gotad; J. Stockton Jenkins; Wade Wilkey; Tanner Watts (WACV, 2023)

Probabilistic Offline Policy Ranking with Approximate Bayesian Computation. - Longchao Da; Porter Jenkins; Trevor Schwantes; Jeffrey Dotson; Hua Wei 001 (AAAI, 2024)

Personalized Product Assortment with Real-time 3D Perception and Bayesian Payoff Estimation. - Porter Jenkins; Michael Selander; J. Stockton Jenkins; Andrew Merrill; Kyle Armstrong (KDD, 2024)

Head Tail Open: Open Tailed Classification of Imbalanced Document Data. - Chetan Joshi; Daniel Segrera; Lawry Sorenson; Mark J. Clement; Bryan S. Morse; Porter Jenkins; Taylor Archibald; M. J. Ghorbani (SAI (1), 2024)

On Measuring Calibration of Discrete Probabilistic Neural Networks. - Spencer Young; Porter Jenkins (CoRR, 2024)

Flexible Heteroscedastic Count Regression with Deep Double Poisson Networks. - Spencer Young; Porter Jenkins; Longchao Da; Jeffrey Dotson; Hua Wei 001 (CoRR, 2024)