Embedded MDS codes for multicast streaming. - Ahmed Badr; Rafid Mahmood; Ashish Khisti (ISIT, 2015)

Low delay network streaming under burst losses. - Rafid Mahmood; Ahmed Badr; Ashish Khisti (ISIT, 2016)

Convolutional Codes With Maximum Column Sum Rank for Network Streaming. - Rafid Mahmood; Ahmed Badr; Ashish Khisti (IEEE Trans. Inf. Theory, 2016)

Automated Treatment Planning in Radiation Therapy using Generative Adversarial Networks. - Rafid Mahmood; Aaron Babier; Andrea McNiven; Adam Diamant; Timothy C. Y. Chan (MLHC, 2018)

Interior Point Methods with Adversarial Networks. - Rafid Mahmood; Aaron Babier; Adam Diamant; Timothy C. Y. Chan (CoRR, 2018)

Streaming Codes for Multiplicative-Matrix Channels With Burst Rank Loss. - Rafid Mahmood; Ahmed Badr; Ashish Khisti (IEEE Trans. Inf. Theory, 2018)

The importance of evaluating the complete automated knowledge-based planning pipeline. - Aaron Babier; Rafid Mahmood; Andrea L. McNiven; Adam Diamant; Timothy C. Y. Chan (CoRR, 2019)

OpenKBP: The open-access knowledge-based planning grand challenge. - Aaron Babier; Binghao Zhang; Rafid Mahmood; Kevin L. Moore 002; Thomas G. Purdie; Andrea L. McNiven; Timothy C. Y. Chan (CoRR, 2020)

AutoAudio: Deep Learning for Automatic Audiogram Interpretation. - Matthew G. Crowson; Jong Wook Lee; Amr Hamour; Rafid Mahmood; Aaron Babier; Vincent Lin; Debara L. Tucci; Timothy C. Y. Chan (J. Medical Syst., 2020)

Sampling from the complement of a polyhedron: An MCMC algorithm for data augmentation. - Timothy C. Y. Chan; Adam Diamant; Rafid Mahmood (Oper. Res. Lett., 2020)

An Ensemble Learning Framework for Model Fitting and Evaluation in Inverse Linear Optimization. - Aaron Babier; Timothy C. Y. Chan; Taewoo Lee; Rafid Mahmood; Daria Terekhov (INFORMS J. Optim., 2021)

How Much More Data Do I Need? Estimating Requirements for Downstream Tasks. - Rafid Mahmood; James Lucas; David Acuna; Daiqing Li; Jonah Philion; José M. Álvarez 004; Zhiding Yu; Sanja Fidler; Marc T. Law (CVPR, 2022)

Low-Budget Active Learning via Wasserstein Distance: An Integer Programming Approach. - Rafid Mahmood; Sanja Fidler; Marc T. Law (ICLR, 2022)

Optimizing Data Collection for Machine Learning. - Rafid Mahmood; James Lucas; José M. Álvarez 004; Sanja Fidler; Marc T. Law (NeurIPS, 2022)

OpenKBP-Opt: An international and reproducible evaluation of 76 knowledge-based planning pipelines. - Aaron Babier; Rafid Mahmood; Binghao Zhang; Victor Gabriel Leandro Alves; Ana Maria Barragán-Montero; Joel Beaudry; Carlos E. Cardenas S.; Yankui Chang; Zijie Chen; Jaehee Chun; Kelly Diaz; Harold David Eraso; et al. (CoRR, 2022)

Bridging the Sim2Real gap with CARE: Supervised Detection Adaptation with Conditional Alignment and Reweighting. - Viraj Prabhu; David Acuna; Andrew Liao; Rafid Mahmood; Marc T. Law; Judy Hoffman; Sanja Fidler; James Lucas (CoRR, 2023)

Bridging the Sim2Real gap with CARE: Supervised Detection Adaptation with Conditional Alignment and Reweighting. - Viraj Prabhu; David Acuna; Rafid Mahmood; Marc T. Law; Yuan-Hong Liao; Judy Hoffman; Sanja Fidler; James Lucas (Trans. Mach. Learn. Res., 2023)

Reasoning Paths with Reference Objects Elicit Quantitative Spatial Reasoning in Large Vision-Language Models. - Yuan-Hong Liao; Rafid Mahmood; Sanja Fidler; David Acuna (EMNLP, 2024)

Transferring Labels to Solve Annotation Mismatches Across Object Detection Datasets. - Yuan-Hong Liao; David Acuna; Rafid Mahmood; James Lucas; Viraj Prabhu; Sanja Fidler (ICLR, 2024)

Pricing and Competition for Generative AI. - Rafid Mahmood (NeurIPS, 2024)

Can Feedback Enhance Semantic Grounding in Large Vision-Language Models? - Yuan-Hong Liao; Rafid Mahmood; Sanja Fidler; David Acuna (CoRR, 2024)

AutoScale: Automatic Prediction of Compute-optimal Data Composition for Training LLMs. - Feiyang Kang; Yifan Sun 010; Bingbing Wen; Si Chen 008; Dawn Song; Rafid Mahmood; Ruoxi Jia 001 (CoRR, 2024)

No Need to Sacrifice Data Quality for Quantity: Crowd-Informed Machine Annotation for Cost-Effective Understanding of Visual Data. - Christopher Klugmann; Rafid Mahmood; Guruprasad Hegde; Amit Kale; Daniel Kondermann (CoRR, 2024)

Uncertainty Estimation for 3D Object Detection via Evidential Learning. - Nikita Durasov; Rafid Mahmood; Jiwoong Choi; Marc T. Law; James Lucas; Pascal Fua; José M. Álvarez 004 (CoRR, 2024)

Can Large Vision-Language Models Correct Semantic Grounding Errors By Themselves? - Yuan-Hong Liao; Rafid Mahmood; Sanja Fidler; David Acuna (CVPR, 2025)

Inverse Optimization: Theory and Applications. - Timothy C. Y. Chan; Rafid Mahmood; Ian Yihang Zhu (Oper. Res., 2025)

Learning to Optimize Contextually Constrained Problems for Real-Time Decision Generation. - Aaron Babier; Timothy C. Y. Chan; Adam Diamant; Rafid Mahmood (Manag. Sci., 2025)

Minority Reports: Balancing Cost and Quality in Ground Truth Data Annotation. - Hsuan Wei Liao; Christopher Klugmann; Daniel Kondermann; Rafid Mahmood (CoRR, 2025)

AdaDeDup: Adaptive Hybrid Data Pruning for Efficient Large-Scale Object Detection Training. - Feiyang Kang; Nadine Chang; Maying Shen; Marc T. Law; Rafid Mahmood; Ruoxi Jia 001; José M. Álvarez 004 (CoRR, 2025)