Boris N. Oreshkin

80 papers A* 10A 1B 1C 4Misc 3Journal 52Unranked 9

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Any-quantile probabilistic forecasting of short-term electricity demand: Fusing uncertainties from diverse sources. Inf. Fusion Slawek Smyl, Boris N. Oreshkin, Pawel Pelka, Grzegorz Dudek
2026	J	`jnl`	Probabilistic Pretraining for Improved Neural Regression. Trans. Mach. Learn. Res. Boris N. Oreshkin, Shiv Kumar Tavker, Dmitry Efimov
2026	J	`jnl`	Time-Aware Prior Fitted Networks for Zero-Shot Forecasting with Exogenous Variables. CoRR Andres Potapczynski, Ravi Kiran Selvam, Tatiana Konstantinova, Shankar Ramasubramanian, Malcolm Wolff, Kin G. Olivares, Ruijun Ma, Mengfei Cao, Michael W. Mahoney, Andrew Gordon Wilson, Boris N. Oreshkin, Dmitry Efimov
2026	J	`jnl`	Zero-shot Forecasting by Simulation Alone. CoRR Boris N. Oreshkin, Mayank Jauhari, Ravi Kiran Selvam, Malcolm Wolff, Wenhao Pan, Shankar Ramasubramanian, Kin G. Olivares, Tatiana Konstantinova, Andres Potapczynski, Mengfei Cao, Dmitry Efimov, Michael W. Mahoney, Andrew Gordon Wilson
2025	J	`jnl`	A Realistic Evaluation of Cross-Frequency Transfer Learning and Foundation Forecasting Models. CoRR Kin G. Olivares, Malcolm Wolff, Tatiana Konstantinova, Shankar Ramasubramanian, Andrew Gordon Wilson, Andres Potapczynski, Willa Potosnak, Mengfei Cao, Boris N. Oreshkin, Dmitry Efimov
2025	—	`conf`	Bayesian Koopman Time Series Forecasting. CAMSAP Antonios Valkanas, Theodore Glavas, Boris N. Oreshkin, Mark J. Coates
2025	J	`jnl`	Efficiently Generating Correlated Sample Paths from Multi-step Time Series Foundation Models. CoRR Ethan Baron, Boris N. Oreshkin, Ruijun Ma, Hanyu Zhang, Kari Torkkola, Michael W. Mahoney, Andrew Gordon Wilson, Tatiana Konstantinova
2025	J	`jnl`	Enhanced N-BEATS for mid-term electricity demand forecasting. Appl. Soft Comput. Mateusz Kasprzyk, Pawel Pelka, Boris N. Oreshkin, Grzegorz Dudek
2025	J	`jnl`	Forking-Sequences. CoRR Willa Potosnak, Malcolm Wolff, Boris N. Oreshkin, Mengfei Cao, Michael W. Mahoney, Dmitry Efimov, Kin G. Olivares
2025	A	`conf`	MODL: Multilearner Online Deep Learning. AISTATS Antonios Valkanas, Boris N. Oreshkin, Mark Coates
2025	J	`jnl`	Probabilistic Pretraining for Neural Regression. CoRR Boris N. Oreshkin, Shiv Kumar Tavker, Dmitry Efimov
2025	—	`conf`	Quantile Regression with Large Language Models for Price Prediction. ACL (Findings) Nikhita Vedula, Dushyanta Dhyani, Laleh Jalali, Boris N. Oreshkin, Mohsen Bayati, Shervin Malmasi
2025	J	`jnl`	Quantile Regression with Large Language Models for Price Prediction. CoRR Nikhita Vedula, Dushyanta Dhyani, Laleh Jalali, Boris N. Oreshkin, Mohsen Bayati, Shervin Malmasi
2025	A*	`conf`	SKOLR: Structured Koopman Operator Linear RNN for Time-Series Forecasting. ICML Yitian Zhang, Liheng Ma, Antonios Valkanas, Boris N. Oreshkin, Mark Coates
2025	J	`jnl`	SKOLR: Structured Koopman Operator Linear RNN for Time-Series Forecasting. CoRR Yitian Zhang, Liheng Ma, Antonios Valkanas, Boris N. Oreshkin, Mark Coates
2025	J	`jnl`	TAT: Temporal-Aligned Transformer for Multi-Horizon Peak Demand Forecasting. CoRR Zhiyuan Zhao, Sitan Yang, Kin G. Olivares, Boris N. Oreshkin, Stan Vitebsky, Michael W. Mahoney, B. Aditya Prakash, Dmitry Efimov
2024	J	`jnl`	Any-Quantile Probabilistic Forecasting of Short-Term Electricity Demand. CoRR Slawek Smyl, Boris N. Oreshkin, Pawel Pelka, Grzegorz Dudek
2024	J	`jnl`	Dynamic layer selection in decoder-only transformers. CoRR Theodore Glavas, Joud Chataoui, Florence Regol, Wassim Jabbour, Antonios Valkanas, Boris N. Oreshkin, Mark Coates
2024	J	`jnl`	Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting. CoRR Mateusz Kasprzyk, Pawel Pelka, Boris N. Oreshkin, Grzegorz Dudek
2024	J	`jnl`	MODL: Multilearner Online Deep Learning. CoRR Antonios Valkanas, Boris N. Oreshkin, Mark Coates
2024	J	`jnl`	Motion In-Betweening via Deep $\Delta$Δ-Interpolator. IEEE Trans. Vis. Comput. Graph. Boris N. Oreshkin, Antonios Valkanas, Félix G. Harvey, Louis-Simon Ménard, Florent Bocquelet, Mark J. Coates
2024	J	`jnl`	♠ SPADE ♠ Split Peak Attention DEcomposition. CoRR 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
2023	J	`jnl`	3D Human Pose and Shape Estimation via HybrIK-Transformer. CoRR Boris N. Oreshkin
2023	A*	`conf`	NHITS: Neural Hierarchical Interpolation for Time Series Forecasting. AAAI Cristian Challu, Kin G. Olivares, Boris N. Oreshkin, Federico Garza Ramírez, Max Mergenthaler Canseco, Artur Dubrawski
2022	J	`jnl`	Motion Inbetweening via Deep Δ-Interpolator. CoRR Boris N. Oreshkin, Antonios Valkanas, Félix G. Harvey, Louis-Simon Ménard, Florent Bocquelet, Mark J. Coates
2022	J	`jnl`	N-HiTS: Neural Hierarchical Interpolation for Time Series Forecasting. CoRR Cristian Challu, Kin G. Olivares, Boris N. Oreshkin, Federico Garza, Max Mergenthaler, Artur Dubrawski
2022	A*	`conf`	ProtoRes: Proto-Residual Network for Pose Authoring via Learned Inverse Kinematics. ICLR Boris N. Oreshkin, Florent Bocquelet, Félix G. Harvey, Bay Raitt, Dominic Laflamme
2022	—	`conf`	SMPL-IK: Learned Morphology-Aware Inverse Kinematics for AI Driven Artistic Workflows. SIGGRAPH Asia Technical Communications Vikram Voleti, Boris N. Oreshkin, Florent Bocquelet, Félix G. Harvey, Louis-Simon Ménard, Christopher Pal
2022	J	`jnl`	SMPL-IK: Learned Morphology-Aware Inverse Kinematics for AI Driven Artistic Workflows. CoRR Vikram Voleti, Boris N. Oreshkin, Florent Bocquelet, Félix G. Harvey, Louis-Simon Ménard, Christopher Pal
2021	A*	`conf`	FC-GAGA: Fully Connected Gated Graph Architecture for Spatio-Temporal Traffic Forecasting. AAAI Boris N. Oreshkin, Arezou Amini, Lucy Coyle, Mark Coates
2021	A*	`conf`	Meta-Learning Framework with Applications to Zero-Shot Time-Series Forecasting. AAAI Boris N. Oreshkin, Dmitri Carpov, Nicolas Chapados, Yoshua Bengio
2021	J	`jnl`	Neural forecasting at scale. CoRR Philippe Chatigny, Shengrui Wang, Jean-Marc Patenaude, Boris N. Oreshkin
2021	J	`jnl`	ProtoRes: Proto-Residual Architecture for Deep Modeling of Human Pose. CoRR Boris N. Oreshkin, Florent Bocquelet, Félix G. Harvey, Bay Raitt, Dominic Laflamme
2020	J	`jnl`	Adaptive filters for the moving target indicator system. CoRR Boris N. Oreshkin
2020	—	`conf`	CLAREL: Classification via retrieval loss for zero-shot learning. CVPR Workshops Boris N. Oreshkin, Negar Rostamzadeh, Pedro O. Pinheiro, Christopher J. Pal
2020	J	`jnl`	FC-GAGA: Fully Connected Gated Graph Architecture for Spatio-Temporal Traffic Forecasting. CoRR Boris N. Oreshkin, Arezou Amini, Lucy Coyle, Mark J. Coates
2020	J	`jnl`	Meta-learning framework with applications to zero-shot time-series forecasting. CoRR Boris N. Oreshkin, Dmitri Carpov, Nicolas Chapados, Yoshua Bengio
2020	J	`jnl`	N-BEATS neural network for mid-term electricity load forecasting. CoRR Boris N. Oreshkin, Grzegorz Dudek, Pawel Pelka
2020	A*	`conf`	N-BEATS: Neural basis expansion analysis for interpretable time series forecasting. ICLR Boris N. Oreshkin, Dmitri Carpov, Nicolas Chapados, Yoshua Bengio
2020	J	`jnl`	Optimization of loading factor preventing target cancellation. CoRR Boris N. Oreshkin, Peter A. Bakulev
2020	J	`jnl`	Optimization over Random and Gradient Probabilistic Pixel Sampling for Fast, Robust Multi-Resolution Image Registration. CoRR Boris N. Oreshkin, Tal Arbel
2020	J	`jnl`	Uncertainty driven probabilistic voxel selection for image registration. CoRR Boris N. Oreshkin, Tal Arbel
2020	A*	`conf`	Weakly Supervised Few-shot Object Segmentation using Co-Attention with Visual and Semantic Embeddings. IJCAI Mennatullah Siam, Naren Doraiswamy, Boris N. Oreshkin, Hengshuai Yao, Martin Jägersand
2020	J	`jnl`	Weakly Supervised Few-shot Object Segmentation using Co-Attention with Visual and Semantic Inputs. CoRR Mennatullah Siam, Naren Doraiswamy, Boris N. Oreshkin, Hengshuai Yao, Martin Jägersand
2019	A*	`conf`	AMP: Adaptive Masked Proxies for Few-Shot Segmentation. ICCV Mennatullah Siam, Boris N. Oreshkin, Martin Jägersand
2019	J	`jnl`	Adaptive Cross-Modal Few-Shot Learning. CoRR Chen Xing, Negar Rostamzadeh, Boris N. Oreshkin, Pedro O. Pinheiro
2019	A*	`conf`	Adaptive Cross-Modal Few-shot Learning. NeurIPS Chen Xing, Negar Rostamzadeh, Boris N. Oreshkin, Pedro O. Pinheiro
2019	J	`jnl`	Adaptive Masked Weight Imprinting for Few-Shot Segmentation. CoRR Mennatullah Siam, Boris N. Oreshkin
2019	J	`jnl`	DECoVaC: Design of Experiments with Controlled Variability Components. CoRR Thomas Boquet, Laure Delisle, Denis Kochetkov, Nathan Schucher, Parmida Atighehchian, Boris N. Oreshkin, Julien Cornebise
2019	J	`jnl`	Fine-grained zero-shot recognition with metric rescaling. CoRR Boris N. Oreshkin, Negar Rostamzadeh, Pedro O. Pinheiro, Christopher J. Pal
2019	J	`jnl`	N-BEATS: Neural basis expansion analysis for interpretable time series forecasting. CoRR Boris N. Oreshkin, Dmitri Carpov, Nicolas Chapados, Yoshua Bengio
2019	J	`jnl`	One-Shot Weakly Supervised Video Object Segmentation. CoRR Mennatullah Siam, Naren Doraiswamy, Boris N. Oreshkin, Hengshuai Yao, Martin Jägersand
2019	—	`conf`	Reproducibility and Stability Analysis in Metric-Based Few-Shot Learning. RML@ICLR Thomas Boquet, Laure Delisle, Denis Kochetkov, Nathan Schucher, Boris N. Oreshkin, Julien Cornebise
2018	A*	`conf`	TADAM: Task dependent adaptive metric for improved few-shot learning. NeurIPS Boris N. Oreshkin, Pau Rodríguez López, Alexandre Lacoste
2018	J	`jnl`	TADAM: Task dependent adaptive metric for improved few-shot learning. CoRR Boris N. Oreshkin, Pau Rodríguez López, Alexandre Lacoste
2018	J	`jnl`	Uncertainty in Multitask Transfer Learning. CoRR Alexandre Lacoste, Boris N. Oreshkin, Wonchang Chung, Thomas Boquet, Negar Rostamzadeh, David Krueger
2017	J	`jnl`	Deep Prior. CoRR Alexandre Lacoste, Thomas Boquet, Negar Rostamzadeh, Boris N. Oreshkin, Wonchang Chung, David Krueger
2017	J	`jnl`	Random numbers for parallel computers: Requirements and methods, with emphasis on GPUs. Math. Comput. Simul. Pierre L'Ecuyer, David Munger, Boris N. Oreshkin, Richard J. Simard
2016	J	`jnl`	Rate-Based Daily Arrival Process Models with Application to Call Centers. Oper. Res. Boris N. Oreshkin, Nazim Régnard, Pierre L'Ecuyer
2013	J	`jnl`	Microwave Radar and Microwave-Induced Thermoacoustics: Dual-Modality Approach for Breast Cancer Detection. IEEE Trans. Biomed. Eng. Evgeny Kirshin, Boris N. Oreshkin, Kevin Guangran Zhu, Milica Popovic, Mark Coates
2013	J	`jnl`	Uncertainty Driven Probabilistic Voxel Selection for Image Registration. IEEE Trans. Medical Imaging Boris N. Oreshkin, Tal Arbel
2012	—	`conf`	Optimization over Random and Gradient Probabilistic Pixel Sampling for Fast, Robust Multi-resolution Image Registration. WBIR Boris N. Oreshkin, Tal Arbel
2011	J	`jnl`	Efficient Delay-Tolerant Particle Filtering. IEEE Trans. Signal Process. Boris N. Oreshkin, Xuan Liu, M. J. Coates
2011	—	`conf`	Fusing microwave radar and microwave-induced thermoacoustics for breast cancer detection. ISBI Evgeny Kirshin, Boris N. Oreshkin, Kevin Guangran Zhu, Milica Popovic, Mark Coates
2011	B	`conf`	Spatial and probabilistic codebook template based head pose estimation from unconstrained environments. ICIP Meltem Demirkus, Boris N. Oreshkin, James J. Clark, Tal Arbel
2010	C	`conf`	Asynchronous distributed particle filter via decentralized evaluation of Gaussian products. FUSION Boris N. Oreshkin, M. J. Coates
2010	J	`jnl`	Efficient delay-tolerant particle filtering CoRR Boris N. Oreshkin, Xuan Liu, Mark Coates
2010	C	`conf`	Efficient delay-tolerant particle filtering through selective processing of out-of-sequence measurements. FUSION Xuan Liu, Boris N. Oreshkin, M. J. Coates
2010	J	`jnl`	Greedy gossip with eavesdropping. IEEE Trans. Signal Process. Deniz Üstebay, Boris N. Oreshkin, Mark Coates, Michael G. Rabbat
2010	J	`jnl`	Optimization and analysis of distributed averaging with short node memory. IEEE Trans. Signal Process. Boris N. Oreshkin, Mark Coates, Michael G. Rabbat
2009	J	`jnl`	Accelerated Distributed Average Consensus via Localized Node State Prediction. IEEE Trans. Signal Process. Tuncer C. Aysal, Boris N. Oreshkin, M. J. Coates
2009	J	`jnl`	Greedy Gossip with Eavesdropping CoRR Deniz Üstebay, Boris N. Oreshkin, Mark Coates, Michael G. Rabbat
2009	C	`conf`	Multi-hop Greedy Gossip with Eavesdropping. FUSION Deniz Üstebay, Boris N. Oreshkin, Mark Coates, Michael G. Rabbat
2009	J	`jnl`	Optimization and Analysis of Distributed Averaging with Short Node Memory CoRR Boris N. Oreshkin, Mark Coates, Michael G. Rabbat
2009	—	`conf`	Optimization and analysis of distributed averaging with memory. Allerton Boris N. Oreshkin, Mark J. Coates, Michael G. Rabbat
2009	Misc	`conf`	The speed of greed: Characterizing myopic gossip through network voracity. ICASSP Deniz Üstebay, Boris N. Oreshkin, Mark Coates, Michael G. Rabbat
2008	Misc	`conf`	Distributed average consensus with increased convergence rate. ICASSP Boris N. Oreshkin, Tuncer C. Aysal, Mark Coates
2008	Misc	`conf`	Optimization of loading factor preventing target cancellation. ICASSP Boris N. Oreshkin, Peter A. Bakulev
2008	—	`conf`	Rates of convergence for greedy gossip with eavesdropping. Allerton Deniz Üstebay, Boris N. Oreshkin, Mark Coates, Michael G. Rabbat
2008	C	`conf`	Weak sense Lp error bounds for leader-node distributed particle filters. FUSION Boris N. Oreshkin, Mark Coates