Learning to Rank Using High-Order Information. - Puneet Kumar Dokania; Aseem Behl; C. V. Jawahar; M. Pawan Kumar (ECCV (4), 2014)

Parsimonious Labeling. - Puneet Kumar Dokania; M. Pawan Kumar (ICCV, 2015)

Partial Linearization Based Optimization for Multi-class SVM. - Pritish Mohapatra; Puneet Kumar Dokania; C. V. Jawahar; M. Pawan Kumar (ECCV (5), 2016)

Minding the Gaps for Block Frank-Wolfe Optimization of Structured SVMs. - Anton Osokin; Jean-Baptiste Alayrac; Isabella Lukasewitz; Puneet Kumar Dokania; Simon Lacoste-Julien (ICML, 2016)

Mining Pixels: Weakly Supervised Semantic Segmentation Using Image Labels. - Qinbin Hou; Puneet Kumar Dokania; Daniela Massiceti; Yunchao Wei; Ming-Ming Cheng; Philip H. S. Torr (CoRR, 2016)

Rounding-based Moves for Semi-Metric Labeling. - M. Pawan Kumar; Puneet Kumar Dokania (J. Mach. Learn. Res., 2016)

High-Order Inference, Ranking, and Regularization Path for Structured SVM. (Inférence d'ordre supérieur, Classement, et Chemin de Régularisation pour les SVM Structurés). - Puneet Kumar Dokania (2016)

Discovering Class-Specific Pixels for Weakly-Supervised Semantic Segmentation. - Arslan Chaudhry; Puneet Kumar Dokania; Philip H. S. Torr (BMVC, 2017)

Bottom-Up Top-Down Cues for Weakly-Supervised Semantic Segmentation. - Qibin Hou; Daniela Massiceti; Puneet Kumar Dokania; Yunchao Wei; Ming-Ming Cheng; Philip H. S. Torr (EMMCVPR, 2017)

Deformable Registration Through Learning of Context-Specific Metric Aggregation. - Enzo Ferrante; Puneet Kumar Dokania; Rafael Marini; Nikos Paragios (MLMI@MICCAI, 2017)

Multi-Agent Diverse Generative Adversarial Networks. - Arnab Ghosh; Viveka Kulharia; Vinay P. Namboodiri; Philip H. S. Torr; Puneet Kumar Dokania (CVPR, 2018)

FlipDial: A Generative Model for Two-Way Visual Dialogue. - Daniela Massiceti; N. Siddharth 001; Puneet Kumar Dokania; Philip H. S. Torr (CVPR, 2018)

Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence. - Arslan Chaudhry; Puneet Kumar Dokania; Thalaiyasingam Ajanthan; Philip H. S. Torr (ECCV (11), 2018)

Visual Dialogue without Vision or Dialogue. - Daniela Massiceti; Puneet K. Dokania; N. Siddharth 001; Philip H. S. Torr (CoRR, 2018)

Proximal Mean-Field for Neural Network Quantization. - Thalaiyasingam Ajanthan; Puneet K. Dokania; Richard Hartley 001; Philip H. S. Torr (ICCV, 2019)

Interactive Sketch & Fill: Multiclass Sketch-to-Image Translation. - Arnab Ghosh; Richard Zhang 001; Puneet K. Dokania; Oliver Wang; Alexei A. Efros; Philip H. S. Torr; Eli Shechtman (ICCV, 2019)

Continual Learning with Tiny Episodic Memories. - Arslan Chaudhry; Marcus Rohrbach; Mohamed Elhoseiny; Thalaiyasingam Ajanthan; Puneet Kumar Dokania; Philip H. S. Torr; Marc'Aurelio Ranzato (CoRR, 2019)

Weakly Supervised Learning of Metric Aggregations for Deformable Image Registration. - Enzo Ferrante; Puneet Kumar Dokania; Rafael Marini; Nikos Paragios (IEEE J. Biomed. Health Informatics, 2019)

GDumb: A Simple Approach that Questions Our Progress in Continual Learning. - Ameya Prabhu; Philip H. S. Torr; Puneet K. Dokania (ECCV (2), 2020)

Stable Rank Normalization for Improved Generalization in Neural Networks and GANs. - Amartya Sanyal; Philip H. S. Torr; Puneet K. Dokania (ICLR, 2020)

Continual Learning in Low-rank Orthogonal Subspaces. - Arslan Chaudhry; Naeemullah Khan; Puneet K. Dokania; Philip H. S. Torr (NeurIPS, 2020)

Calibrating Deep Neural Networks using Focal Loss. - Jishnu Mukhoti; Viveka Kulharia; Amartya Sanyal; Stuart Golodetz; Philip H. S. Torr; Puneet K. Dokania (NeurIPS, 2020)

A Revised Generative Evaluation of Visual Dialogue. - Daniela Massiceti; Viveka Kulharia; Puneet K. Dokania; N. Siddharth 001; Philip H. S. Torr (CoRR, 2020)

Simulation-Based Inference for Global Health Decisions. - Christian Schröder de Witt; Bradley Gram-Hansen; Nantas Nardelli; Andrew Gambardella; Robert Zinkov; Puneet K. Dokania; N. Siddharth 001; Ana Belen Espinosa-Gonzalez; Ara Darzi; Philip H. S. Torr; Atilim Günes Baydin (CoRR, 2020)

On Batch Normalisation for Approximate Bayesian Inference. - Jishnu Mukhoti; Puneet K. Dokania; Philip H. S. Torr; Yarin Gal (CoRR, 2020)

Using Hindsight to Anchor Past Knowledge in Continual Learning. - Arslan Chaudhry; Albert Gordo; Puneet K. Dokania; Philip H. S. Torr; David Lopez-Paz (AAAI, 2021)

Mirror Descent View for Neural Network Quantization. - Thalaiyasingam Ajanthan; Kartik Gupta; Philip H. S. Torr; Richard Hartley 001; Puneet K. Dokania (AISTATS, 2021)

Progressive Skeletonization: Trimming more fat from a network at initialization. - Pau de Jorge; Amartya Sanyal; Harkirat S. Behl; Philip H. S. Torr; Grégory Rogez; Puneet K. Dokania (ICLR, 2021)

No Cost Likelihood Manipulation at Test Time for Making Better Mistakes in Deep Networks. - Shyamgopal Karthik; Ameya Prabhu; Puneet K. Dokania; Vineet Gandhi (ICLR, 2021)

How Benign is Benign Overfitting ? - Amartya Sanyal; Puneet K. Dokania; Varun Kanade; Philip H. S. Torr (ICLR, 2021)

A Continuous Mapping For Augmentation Design. - Keyu Tian; Chen Lin 003; Ser-Nam Lim; Wanli Ouyang; Puneet K. Dokania; Philip H. S. Torr (NeurIPS, 2021)

Multilevel Knowledge Transfer for Cross-Domain Object Detection. - Botos Csaba; Xiaojuan Qi 001; Arslan Chaudhry; Puneet K. Dokania; Philip H. S. Torr (CoRR, 2021)

A Step Towards Efficient Evaluation of Complex Perception Tasks in Simulation. - Jonathan Sadeghi; Blaine Rogers; James Gunn; Thomas Saunders; Sina Samangooei; Puneet Kumar Dokania; John Redford (CoRR, 2021)

An Impartial Take to the CNN vs Transformer Robustness Contest. - Francesco Pinto; Philip H. S. Torr; Puneet K. Dokania (ECCV (13), 2022)

Make Some Noise: Reliable and Efficient Single-Step Adversarial Training. - Pau de Jorge Aranda; Adel Bibi; Riccardo Volpi; Amartya Sanyal; Philip H. S. Torr; Grégory Rogez; Puneet K. Dokania (NeurIPS, 2022)

Using Mixup as a Regularizer Can Surprisingly Improve Accuracy & Out-of-Distribution Robustness. - Francesco Pinto; Harry Yang; Ser Nam Lim; Philip H. S. Torr; Puneet K. Dokania (NeurIPS, 2022)

Catastrophic overfitting is a bug but also a feature. - Guillermo Ortiz-Jiménez; Pau de Jorge; Amartya Sanyal; Adel Bibi; Puneet K. Dokania; Pascal Frossard; Grégory Rogez; Philip H. S. Torr (CoRR, 2022)

RegMixup: Mixup as a Regularizer Can Surprisingly Improve Accuracy and Out Distribution Robustness. - Francesco Pinto; Harry Yang; Ser-Nam Lim; Philip H. S. Torr; Puneet K. Dokania (CoRR, 2022)

ANCER: Anisotropic Certification via Sample-wise Volume Maximization. - Francisco Eiras; Motasem Alfarra; Philip H. S. Torr; M. Pawan Kumar; Puneet K. Dokania; Bernard Ghanem; Adel Bibi (Trans. Mach. Learn. Res., 2022)

Query-Based Hard-Image Retrieval for Object Detection at Test Time. - Edward Ayers; Jonathan Sadeghi; John Redford; Romain Mueller; Puneet K. Dokania (AAAI, 2023)

Sample-Dependent Adaptive Temperature Scaling for Improved Calibration. - Tom Joy; Francesco Pinto; Ser-Nam Lim; Philip H. S. Torr; Puneet K. Dokania (AAAI, 2023)

Towards Building Self-Aware Object Detectors via Reliable Uncertainty Quantification and Calibration. - Kemal Oksuz; Tom Joy; Puneet K. Dokania (CVPR, 2023)

Computationally Budgeted Continual Learning: What Does Matter? - Ameya Prabhu; Hasan Abed Al Kader Hammoud; Puneet K. Dokania; Philip H. S. Torr; Ser-Nam Lim; Bernard Ghanem; Adel Bibi (CVPR, 2023)

Raising the Bar on the Evaluation of Out-of-Distribution Detection. - Jishnu Mukhoti; Tsung-Yu Lin; Bor-Chun Chen; Ashish Shah; Philip H. S. Torr; Puneet K. Dokania; Ser-Nam Lim (ICCV (Workshops), 2023)

Graph Inductive Biases in Transformers without Message Passing. - Liheng Ma; Chen Lin 003; Derek Lim; Adriana Romero-Soriano; Puneet K. Dokania; Mark Coates; Philip H. S. Torr; Ser-Nam Lim (ICML, 2023)

Online Continual Learning Without the Storage Constraint. - Ameya Prabhu; Zhipeng Cai 003; Puneet K. Dokania; Philip H. S. Torr; Vladlen Koltun; Ozan Sener (CoRR, 2023)

Diagnosing and Preventing Instabilities in Recurrent Video Processing. - Thomas Tanay; Aivar Sootla; Matteo Maggioni; Puneet K. Dokania; Philip H. S. Torr; Ales Leonardis; Gregory G. Slabaugh (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Catastrophic overfitting can be induced with discriminative non-robust features. - Guillermo Ortiz-Jiménez; Pau de Jorge; Amartya Sanyal; Adel Bibi; Puneet K. Dokania; Pascal Frossard; Grégory Rogez; Philip Torr 001 (Trans. Mach. Learn. Res., 2023)

Segment, Select, Correct: A Framework for Weakly-Supervised Referring Segmentation. - Francisco Eiras; Kemal Oksuz; Adel Bibi; Philip H. S. Torr; Puneet K. Dokania (ECCV Workshops (10), 2024)

Placing Objects in Context via Inpainting for Out-of-Distribution Segmentation. - Pau de Jorge; Riccardo Volpi; Puneet K. Dokania; Philip H. S. Torr; Grégory Rogez (ECCV (45), 2024)

On Calibration of Object Detectors: Pitfalls, Evaluation and Baselines. - Selim Kuzucu; Kemal Oksuz; Jonathan Sadeghi; Puneet K. Dokania (ECCV (21), 2024)

What Makes and Breaks Safety Fine-tuning? A Mechanistic Study. - Samyak Jain; Ekdeep Singh Lubana; Kemal Oksuz; Tom Joy; Philip Torr 001; Amartya Sanyal; Puneet K. Dokania (NeurIPS, 2024)

RanDumb: Random Representations Outperform Online Continually Learned Representations. - Ameya Prabhu; Shiven Sinha; Ponnurangam Kumaraguru; Philip Torr 001; Ozan Sener; Puneet K. Dokania (NeurIPS, 2024)

RanDumb: A Simple Approach that Questions the Efficacy of Continual Representation Learning. - Ameya Prabhu; Shiven Sinha; Ponnurangam Kumaraguru; Philip H. S. Torr; Ozan Sener; Puneet K. Dokania (CoRR, 2024)

Fine-tuning can cripple your foundation model; preserving features may be the solution. - Jishnu Mukhoti; Yarin Gal; Philip Torr 001; Puneet K. Dokania (Trans. Mach. Learn. Res., 2024)

MoCaE: Mixture of Calibrated Experts Significantly Improves Object Detection. - Kemal Oksuz; Selim Kuzucu; Tom Joy; Puneet K. Dokania (Trans. Mach. Learn. Res., 2024)

MObI: Multimodal Object Inpainting Using Diffusion Models. - Alexandru Buburuzan; Anuj Sharma; John Redford; Puneet K. Dokania; Romain Mueller (CVPR Workshops, 2025)

AnnoCaseLaw: A Richly-Annotated Dataset For Benchmarking Explainable Legal Judgment Prediction. - Magnus Sesodia; Alina Petrova; John Armour; Thomas Lukasiewicz; Oana-Maria Camburu; Puneet K. Dokania; Philip Torr 001; Christian Schröder de Witt (CoRR, 2025)

Mixture of Experts Made Intrinsically Interpretable. - Xingyi Yang; Constantin Venhoff; Ashkan Khakzar; Christian Schröder de Witt; Puneet K. Dokania; Adel Bibi; Philip Torr 001 (CoRR, 2025)

Modeling Gene Expression Distributional Shifts for Unseen Genetic Perturbations. - Kalyan Ramakrishnan; Jonathan G. Hedley; Sisi Qu; Puneet K. Dokania; Philip H. S. Torr; Cesar A. Prada-Medina; Julien Fauqueur; Kaspar Märtens (CoRR, 2025)