Rates of convergence for greedy gossip with eavesdropping. - Deniz Üstebay; Boris N. Oreshkin; Mark Coates; Michael G. Rabbat (Allerton, 2008)

Weak sense Lp error bounds for leader-node distributed particle filters. - Boris N. Oreshkin; Mark Coates (FUSION, 2008)

Distributed average consensus with increased convergence rate. - Boris N. Oreshkin; Tuncer C. Aysal; Mark Coates (ICASSP, 2008)

Optimization of loading factor preventing target cancellation. - Boris N. Oreshkin; Peter A. Bakulev (ICASSP, 2008)

Optimization and analysis of distributed averaging with memory. - Boris N. Oreshkin; Mark J. Coates; Michael G. Rabbat (Allerton, 2009)

Multi-hop Greedy Gossip with Eavesdropping. - Deniz Üstebay; Boris N. Oreshkin; Mark Coates; Michael G. Rabbat (FUSION, 2009)

The speed of greed: Characterizing myopic gossip through network voracity. - Deniz Üstebay; Boris N. Oreshkin; Mark Coates; Michael G. Rabbat (ICASSP, 2009)

Accelerated Distributed Average Consensus via Localized Node State Prediction. - Tuncer C. Aysal; Boris N. Oreshkin; M. J. Coates (IEEE Trans. Signal Process., 2009)

Efficient delay-tolerant particle filtering through selective processing of out-of-sequence measurements. - Xuan Liu; Boris N. Oreshkin; M. J. Coates (FUSION, 2010)

Asynchronous distributed particle filter via decentralized evaluation of Gaussian products. - Boris N. Oreshkin; M. J. Coates (FUSION, 2010)

Optimization and analysis of distributed averaging with short node memory. - Boris N. Oreshkin; Mark Coates; Michael G. Rabbat (IEEE Trans. Signal Process., 2010)

Greedy gossip with eavesdropping. - Deniz Üstebay; Boris N. Oreshkin; Mark Coates; Michael G. Rabbat (IEEE Trans. Signal Process., 2010)

Spatial and probabilistic codebook template based head pose estimation from unconstrained environments. - Meltem Demirkus; Boris N. Oreshkin; James J. Clark; Tal Arbel (ICIP, 2011)

Fusing microwave radar and microwave-induced thermoacoustics for breast cancer detection. - Evgeny Kirshin; Boris N. Oreshkin; Kevin Guangran Zhu; Milica Popovic; Mark Coates (ISBI, 2011)

Efficient Delay-Tolerant Particle Filtering. - Boris N. Oreshkin; Xuan Liu; M. J. Coates (IEEE Trans. Signal Process., 2011)

Optimization over Random and Gradient Probabilistic Pixel Sampling for Fast, Robust Multi-resolution Image Registration. - Boris N. Oreshkin; Tal Arbel (WBIR, 2012)

Microwave Radar and Microwave-Induced Thermoacoustics: Dual-Modality Approach for Breast Cancer Detection. - Evgeny Kirshin; Boris N. Oreshkin; Kevin Guangran Zhu; Milica Popovic; Mark Coates (IEEE Trans. Biomed. Eng., 2013)

Uncertainty Driven Probabilistic Voxel Selection for Image Registration. - Boris N. Oreshkin; Tal Arbel (IEEE Trans. Medical Imaging, 2013)

Rate-Based Daily Arrival Process Models with Application to Call Centers. - Boris N. Oreshkin; Nazim Régnard; Pierre L'Ecuyer (Oper. Res., 2016)

Deep Prior. - Alexandre Lacoste; Thomas Boquet; Negar Rostamzadeh; Boris N. Oreshkin; Wonchang Chung; David Krueger 001 (CoRR, 2017)

Random numbers for parallel computers: Requirements and methods, with emphasis on GPUs. - Pierre L'Ecuyer; David Munger; Boris N. Oreshkin; Richard J. Simard (Math. Comput. Simul., 2017)

TADAM: Task dependent adaptive metric for improved few-shot learning. - Boris N. Oreshkin; Pau Rodríguez López; Alexandre Lacoste (NeurIPS, 2018)

Uncertainty in Multitask Transfer Learning. - Alexandre Lacoste; Boris N. Oreshkin; Wonchang Chung; Thomas Boquet; Negar Rostamzadeh; David Krueger 001 (CoRR, 2018)

AMP: Adaptive Masked Proxies for Few-Shot Segmentation. - Mennatullah Siam; Boris N. Oreshkin; Martin Jägersand (ICCV, 2019)

Reproducibility and Stability Analysis in Metric-Based Few-Shot Learning. - Thomas Boquet; Laure Delisle; Denis Kochetkov; Nathan Schucher; Boris N. Oreshkin; Julien Cornebise (RML@ICLR, 2019)

Adaptive Cross-Modal Few-shot Learning. - Chen Xing; Negar Rostamzadeh; Boris N. Oreshkin; Pedro O. Pinheiro (NeurIPS, 2019)

Adaptive Masked Weight Imprinting for Few-Shot Segmentation. - Mennatullah Siam; Boris N. Oreshkin (CoRR, 2019)

Fine-grained zero-shot recognition with metric rescaling. - Boris N. Oreshkin; Negar Rostamzadeh; Pedro O. Pinheiro; Christopher J. Pal (CoRR, 2019)

DECoVaC: Design of Experiments with Controlled Variability Components. - Thomas Boquet; Laure Delisle; Denis Kochetkov; Nathan Schucher; Parmida Atighehchian; Boris N. Oreshkin; Julien Cornebise (CoRR, 2019)

One-Shot Weakly Supervised Video Object Segmentation. - Mennatullah Siam; Naren Doraiswamy; Boris N. Oreshkin; Hengshuai Yao; Martin Jägersand (CoRR, 2019)

CLAREL: Classification via retrieval loss for zero-shot learning. - Boris N. Oreshkin; Negar Rostamzadeh; Pedro O. Pinheiro; Christopher J. Pal (CVPR Workshops, 2020)

N-BEATS: Neural basis expansion analysis for interpretable time series forecasting. - Boris N. Oreshkin; Dmitri Carpov; Nicolas Chapados; Yoshua Bengio (ICLR, 2020)

Weakly Supervised Few-shot Object Segmentation using Co-Attention with Visual and Semantic Embeddings. - Mennatullah Siam; Naren Doraiswamy; Boris N. Oreshkin; Hengshuai Yao; Martin Jägersand (IJCAI, 2020)

Weakly Supervised Few-shot Object Segmentation using Co-Attention with Visual and Semantic Inputs. - Mennatullah Siam; Naren Doraiswamy; Boris N. Oreshkin; Hengshuai Yao; Martin Jägersand (CoRR, 2020)

N-BEATS neural network for mid-term electricity load forecasting. - Boris N. Oreshkin; Grzegorz Dudek; Pawel Pelka (CoRR, 2020)

Adaptive filters for the moving target indicator system. - Boris N. Oreshkin (CoRR, 2020)

FC-GAGA: Fully Connected Gated Graph Architecture for Spatio-Temporal Traffic Forecasting. - Boris N. Oreshkin; Arezou Amini; Lucy Coyle; Mark Coates (AAAI, 2021)

Meta-Learning Framework with Applications to Zero-Shot Time-Series Forecasting. - Boris N. Oreshkin; Dmitri Carpov; Nicolas Chapados; Yoshua Bengio (AAAI, 2021)

ProtoRes: Proto-Residual Architecture for Deep Modeling of Human Pose. - Boris N. Oreshkin; Florent Bocquelet; Félix G. Harvey; Bay Raitt; Dominic Laflamme (CoRR, 2021)

Neural forecasting at scale. - Philippe Chatigny; Shengrui Wang; Jean-Marc Patenaude; Boris N. Oreshkin (CoRR, 2021)

ProtoRes: Proto-Residual Network for Pose Authoring via Learned Inverse Kinematics. - Boris N. Oreshkin; Florent Bocquelet; Félix G. Harvey; Bay Raitt; Dominic Laflamme (ICLR, 2022)

SMPL-IK: Learned Morphology-Aware Inverse Kinematics for AI Driven Artistic Workflows. - Vikram Voleti; Boris N. Oreshkin; Florent Bocquelet; Félix G. Harvey; Louis-Simon Ménard; Christopher Pal (SIGGRAPH Asia Technical Communications, 2022)

Motion Inbetweening via Deep Δ-Interpolator. - Boris N. Oreshkin; Antonios Valkanas; Félix G. Harvey; Louis-Simon Ménard; Florent Bocquelet; Mark J. Coates (CoRR, 2022)

N-HiTS: Neural Hierarchical Interpolation for Time Series Forecasting. - Cristian Challu; Kin G. Olivares; Boris N. Oreshkin; Federico Garza; Max Mergenthaler; Artur Dubrawski (CoRR, 2022)

NHITS: Neural Hierarchical Interpolation for Time Series Forecasting. - Cristian Challu; Kin G. Olivares; Boris N. Oreshkin; Federico Garza Ramírez; Max Mergenthaler Canseco; Artur Dubrawski (AAAI, 2023)

3D Human Pose and Shape Estimation via HybrIK-Transformer. - Boris N. Oreshkin (CoRR, 2023)

Any-Quantile Probabilistic Forecasting of Short-Term Electricity Demand. - Slawek Smyl; Boris N. Oreshkin; Pawel Pelka; Grzegorz Dudek (CoRR, 2024)

Dynamic layer selection in decoder-only transformers. - Theodore Glavas; Joud Chataoui; Florence Regol; Wassim Jabbour; Antonios Valkanas; Boris N. Oreshkin; Mark Coates (CoRR, 2024)

♠ SPADE ♠ Split Peak Attention DEcomposition. - Malcolm Wolff; Kin G. Olivares; Boris N. Oreshkin; Sunny Ruan; Sitan Yang; Abhinav Katoch; Shankar Ramasubramanian; Youxin Zhang; Michael W. Mahoney; Dmitry Efimov; Vincent Quenneville-Bélair (CoRR, 2024)

Motion In-Betweening via Deep $ Delta$Δ-Interpolator. - Boris N. Oreshkin; Antonios Valkanas; Félix G. Harvey; Louis-Simon Ménard; Florent Bocquelet; Mark J. Coates (IEEE Trans. Vis. Comput. Graph., 2024)

Quantile Regression with Large Language Models for Price Prediction. - Nikhita Vedula; Dushyanta Dhyani; Laleh Jalali; Boris N. Oreshkin; Mohsen Bayati; Shervin Malmasi (ACL (Findings), 2025)

MODL: Multilearner Online Deep Learning. - Antonios Valkanas; Boris N. Oreshkin; Mark Coates (AISTATS, 2025)

Enhanced N-BEATS for mid-term electricity demand forecasting. - Mateusz Kasprzyk; Pawel Pelka; Boris N. Oreshkin; Grzegorz Dudek (Appl. Soft Comput., 2025)

SKOLR: Structured Koopman Operator Linear RNN for Time-Series Forecasting. - Yitian Zhang; Liheng Ma; Antonios Valkanas; Boris N. Oreshkin; Mark Coates (CoRR, 2025)

TAT: Temporal-Aligned Transformer for Multi-Horizon Peak Demand Forecasting. - Zhiyuan Zhao 002; Sitan Yang; Kin G. Olivares; Boris N. Oreshkin; Stan Vitebsky; Michael W. Mahoney; B. Aditya Prakash; Dmitry Efimov (CoRR, 2025)