Gaussian sum particle flow filter. - Soumyasundar Pal; Mark Coates (CAMSAP, 2017)

Particle Flow Particle Filter for Gaussian Mixture Noise Models. - Soumyasundar Pal; Mark Coates (ICASSP, 2018)

Sequential MCMC With The Discrete Bouncy Particle Sampler. - Soumyasundar Pal; Mark Coates (SSP, 2018)

Bayesian Graph Convolutional Neural Networks for Semi-Supervised Classification. - Yingxue Zhang 001; Soumyasundar Pal; Mark Coates; Deniz Üstebay (AAAI, 2019)

Particle Flow Particle Filter using Gromov's method. - Soumyasundar Pal; Mark Coates (CAMSAP, 2019)

Node Copying for Protection Against Graph Neural Network Topology Attacks. - Florence Regol; Soumyasundar Pal; Mark Coates (CAMSAP, 2019)

Scalable MCMC in Degree Corrected Stochastic Block Model. - Soumyasundar Pal; Mark Coates (ICASSP, 2019)

Bayesian Graph Convolutional Neural Networks Using Non-Parametric Graph Learning. - Soumyasundar Pal; Florence Regol; Mark J. Coates (CoRR, 2019)

Bayesian Graph Convolutional Neural Networks using Node Copying. - Soumyasundar Pal; Florence Regol; Mark Coates (CoRR, 2019)

Invertible Particle-Flow-Based Sequential MCMC With Extension to Gaussian Mixture Noise Models. - Yunpeng Li 001; Soumyasundar Pal; Mark J. Coates (IEEE Trans. Signal Process., 2019)

Active Learning on Attributed Graphs via Graph Cognizant Logistic Regression and Preemptive Query Generation. - Florence Regol; Soumyasundar Pal; Yingxue Zhang 001; Mark Coates (ICML, 2020)

Non Parametric Graph Learning for Bayesian Graph Neural Networks. - Soumyasundar Pal; Saber Malekmohammadi; Florence Regol; Yingxue Zhang 001; Yishi Xu; Mark Coates (UAI, 2020)

Detection and Defense of Topological Adversarial Attacks on Graphs. - Yingxue Zhang 001; Florence Regol; Soumyasundar Pal; Sakif Khan; Liheng Ma; Mark Coates (AISTATS, 2021)

RNN with Particle Flow for Probabilistic Spatio-temporal Forecasting. - Soumyasundar Pal; Liheng Ma; Yingxue Zhang 001; Mark Coates (ICML, 2021)

Bag Graph: Multiple Instance Learning Using Bayesian Graph Neural Networks. - Soumyasundar Pal; Antonios Valkanas; Florence Regol; Mark Coates (AAAI, 2022)

Node copying: A random graph model for effective graph sampling. - Florence Regol; Soumyasundar Pal; Jianing Sun; Yingxue Zhang 001; Yanhui Geng; Mark Coates (Signal Process., 2022)

Multi-resolution Time-Series Transformer for Long-term Forecasting. - Yitian Zhang; Liheng Ma; Soumyasundar Pal; Yingxue Zhang 001; Mark Coates (AISTATS, 2024)

CKGConv: General Graph Convolution with Continuous Kernels. - Liheng Ma; Soumyasundar Pal; Yitian Zhang; Jiaming Zhou; Yingxue Zhang 001; Mark Coates (ICML, 2024)

Enhancing Logical Reasoning in Large Language Models through Graph-based Synthetic Data. - Jiaming Zhou; Abbas Ghaddar; Ge Zhang; Liheng Ma; Yaochen Hu 001; Soumyasundar Pal; Mark Coates; Bin Wang 034; Yingxue Zhang 001; Jianye Hao (CoRR, 2024)

Hint Marginalization for Improved Reasoning in Large Language Models. - Soumyasundar Pal; Didier Chételat; Yingxue Zhang 001; Mark Coates (CoRR, 2024)

Population Monte Carlo With Normalizing Flow. - Soumyasundar Pal; Antonios Valkanas; Mark Coates (IEEE Signal Process. Lett., 2024)

Simplifying Graph Transformers. - Liheng Ma; Soumyasundar Pal; Yingxue Zhang 001; Philip H. S. Torr; Mark Coates (CoRR, 2025)

Reasoning on a Budget: A Survey of Adaptive and Controllable Test-Time Compute in LLMs. - Mohammad Ali Alomrani; Yingxue Zhang 001; Derek Li; Qianyi Sun; Soumyasundar Pal; Zhanguang Zhang; Yaochen Hu 001; Rohan Deepak Ajwani; Antonios Valkanas; Raika Karimi; Peng Cheng; Yunzhou Wang; et al. (CoRR, 2025)