Multi-template Scale-Adaptive Kernelized Correlation Filters. - Adel Bibi; Bernard Ghanem (ICCV Workshops, 2015)

3D Part-Based Sparse Tracker with Automatic Synchronization and Registration. - Adel Bibi; Tianzhu Zhang 001; Bernard Ghanem (CVPR, 2016)

In Defense of Sparse Tracking: Circulant Sparse Tracker. - Tianzhu Zhang 001; Adel Bibi; Bernard Ghanem (CVPR, 2016)

Target Response Adaptation for Correlation Filter Tracking. - Adel Bibi; Matthias Mueller 001; Bernard Ghanem (ECCV (6), 2016)

FFTLasso: Large-Scale LASSO in the Fourier Domain. - Adel Bibi; Hani Itani; Bernard Ghanem (CVPR, 2017)

High Order Tensor Formulation for Convolutional Sparse Coding. - Adel Bibi; Bernard Ghanem (ICCV, 2017)

Analytic Expressions for Probabilistic Moments of PL-DNN With Gaussian Input. - Adel Bibi; Modar Alfadly; Bernard Ghanem (CVPR, 2018)

TrackingNet: A Large-Scale Dataset and Benchmark for Object Tracking in the Wild. - Matthias Müller 011; Adel Bibi; Silvio Giancola; Salman Al-Subaihi; Bernard Ghanem (ECCV (1), 2018)

Deep Layers as Stochastic Solvers. - Adel Bibi; Bernard Ghanem; Vladlen Koltun; René Ranftl (ICLR (Poster), 2019)

Local Color Mapping Combined with Color Transfer for Underwater Image Enhancement. - Rafal Protasiuk; Adel Bibi; Bernard Ghanem (WACV, 2019)

Analytical Moment Regularizer for Gaussian Robust Networks. - Modar Alfadly; Adel Bibi; Bernard Ghanem (CoRR, 2019)

Probabilistically True and Tight Bounds for Robust Deep Neural Network Training. - Salman Al-Subaihi; Adel Bibi; Modar Alfadly; Bernard Ghanem (CoRR, 2019)

Constrained K-means with General Pairwise and Cardinality Constraints. - Adel Bibi; Baoyuan Wu; Bernard Ghanem (CoRR, 2019)

Robust Gabor Networks. - Juan C. Pérez; Motasem Alfarra; Guillaume Jeanneret; Adel Bibi; Ali K. Thabet; Bernard Ghanem; Pablo Arbeláez (CoRR, 2019)

A Stochastic Derivative-Free Optimization Method with Importance Sampling: Theory and Learning to Control. - Adel Bibi; El Houcine Bergou; Ozan Sener; Bernard Ghanem; Peter Richtárik (AAAI, 2020)

Gabor Layers Enhance Network Robustness. - Juan C. Pérez; Motasem Alfarra; Guillaume Jeanneret; Adel Bibi; Ali K. Thabet; Bernard Ghanem; Pablo Arbeláez (ECCV (9), 2020)

A Stochastic Derivative Free Optimization Method with Momentum. - Eduard Gorbunov; Adel Bibi; Ozan Sener; El Houcine Bergou; Peter Richtárik (ICLR, 2020)

On the Decision Boundaries of Deep Neural Networks: A Tropical Geometry Perspective. - Motasem Alfarra; Adel Bibi; Hasan Hammoud; Mohamed Gaafar; Bernard Ghanem (CoRR, 2020)

ClusTR: Clustering Training for Robustness. - Motasem Alfarra; Juan C. Pérez; Adel Bibi; Ali K. Thabet; Pablo Arbeláez; Bernard Ghanem (CoRR, 2020)

Network Moments: Extensions and Sparse-Smooth Attacks. - Modar Alfadly; Adel Bibi; Emilio Botero; Salman Al-Subaihi; Bernard Ghanem (CoRR, 2020)

Understanding a Block of Layers in Deep Neural Networks: Optimization, Probabilistic and Tropical Geometric Perspectives. - Adel Bibi (2020)

Rethinking Clustering for Robustness. - Motasem Alfarra; Juan C. Pérez; Adel Bibi; Ali K. Thabet; Pablo Arbeláez; Bernard Ghanem (BMVC, 2021)

DeformRS: Certifying Input Deformations with Randomized Smoothing. - Motasem Alfarra; Adel Bibi; Naeemullah Khan; Philip H. S. Torr; Bernard Ghanem (AAAI, 2022)

Combating Adversaries with Anti-adversaries. - Motasem Alfarra; Juan C. Pérez; Ali K. Thabet; Adel Bibi; Philip H. S. Torr; Bernard Ghanem (AAAI, 2022)

Diversified Dynamic Routing for Vision Tasks. - Botos Csaba; Adel Bibi; Yanwei Li; Philip H. S. Torr; Ser-Nam Lim (ECCV Workshops (4), 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)

Data dependent randomized smoothing. - Motasem Alfarra; Adel Bibi; Philip H. S. Torr; Bernard Ghanem (UAI, 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)

Illusionary Attacks on Sequential Decision Makers and Countermeasures. - Tim Franzmeyer; João F. Henriques; Jakob N. Foerster; Philip H. S. Torr; Adel Bibi; Christian Schröder de Witt (CoRR, 2022)

SimCS: Simulation for Online Domain-Incremental Continual Segmentation. - Motasem Alfarra; Zhipeng Cai; Adel Bibi; Bernard Ghanem; Matthias Müller 011 (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)

Real-Time Evaluation in Online Continual Learning: A New Hope. - Yasir Ghunaim; Adel Bibi; Kumail Alhamoud; Motasem Alfarra; Hasan Abed Al Kader Hammoud; Ameya Prabhu; Philip H. S. Torr; Bernard Ghanem (CVPR, 2023)

Don't FREAK Out: A Frequency-Inspired Approach to Detecting Backdoor Poisoned Samples in DNNs. - Hasan Abed Al Kader Hammoud; Adel Bibi; Philip H. S. Torr; Bernard Ghanem (CVPR Workshops, 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)

Rapid Adaptation in Online Continual Learning: Are We Evaluating It Right? - Hasan Abed Al Kader Hammoud; Ameya Prabhu; Ser-Nam Lim; Philip H. S. Torr; Adel Bibi; Bernard Ghanem (ICCV, 2023)

Certifying Ensembles: A General Certification Theory with S-Lipschitzness. - Aleksandar Petrov; Francisco Eiras; Amartya Sanyal; Philip H. S. Torr; Adel Bibi (ICML, 2023)

Language Model Tokenizers Introduce Unfairness Between Languages. - Aleksandar Petrov; Emanuele La Malfa; Philip H. S. Torr; Adel Bibi (NeurIPS, 2023)

RANCER: Non-Axis Aligned Anisotropic Certification with Randomized Smoothing. - Taras Rumezhak; Francisco Girbal Eiras; Philip H. S. Torr; Adel Bibi (WACV, 2023)

Constrained Clustering: General Pairwise and Cardinality Constraints. - Adel Bibi; Ali Alqahtani 001; Bernard Ghanem (IEEE Access, 2023)

Real-Time Evaluation in Online Continual Learning: A New Paradigm. - Yasir Ghunaim; Adel Bibi; Kumail Alhamoud; Motasem Alfarra; Hasan Abed Al Kader Hammoud; Ameya Prabhu; Philip H. S. Torr; Bernard Ghanem (CoRR, 2023)

Provably Correct Physics-Informed Neural Networks. - Francisco Eiras; Adel Bibi; Rudy Bunel; Krishnamurthy (Dj) Dvijotham; Philip H. S. Torr; M. Pawan Kumar (CoRR, 2023)

From Categories to Classifier: Name-Only Continual Learning by Exploring the Web. - Ameya Prabhu; Hasan Abed Al Kader Hammoud; Ser-Nam Lim; Bernard Ghanem; Philip H. S. Torr; Adel Bibi (CoRR, 2023)

Label Delay in Continual Learning. - Botos Csaba; Wenxuan Zhang 001; Matthias Müller 011; Ser-Nam Lim; Mohamed Elhoseiny; Philip H. S. Torr; Adel Bibi (CoRR, 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)

On the Decision Boundaries of Neural Networks: A Tropical Geometry Perspective. - Motasem Alfarra; Adel Bibi; Hasan Hammoud; Mohamed Gaafar; Bernard Ghanem (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

SimCS: Simulation for Domain Incremental Online Continual Segmentation. - Motasem Alfarra; Zhipeng Cai; Adel Bibi; Bernard Ghanem; Matthias Müller 001 (AAAI, 2024)

From Categories to Classifiers: Name-Only Continual Learning by Exploring the Web. - Ameya Prabhu; Hasan Abed Al Kader Hammoud; Ser-Nam Lim; Bernard Ghanem; Philip Torr 001; Adel Bibi (CoLLAs, 2024)

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)

On Pretraining Data Diversity for Self-Supervised Learning. - Hasan Abed Al Kader Hammoud; Tuhin Das; Fabio Pizzati; Philip H. S. Torr; Adel Bibi; Bernard Ghanem (ECCV (56), 2024)

Model Merging and Safety Alignment: One Bad Model Spoils the Bunch. - Hasan Hammoud; Umberto Michieli; Fabio Pizzati; Philip Torr 001; Adel Bibi; Bernard Ghanem; Mete Ozay (EMNLP (Findings), 2024)

Illusory Attacks: Information-theoretic detectability matters in adversarial attacks. - Tim Franzmeyer; Stephen Marcus McAleer; João F. Henriques; Jakob Nicolaus Foerster; Philip Torr 001; Adel Bibi; Christian Schröder de Witt (ICLR, 2024)

When Do Prompting and Prefix-Tuning Work? A Theory of Capabilities and Limitations. - Aleksandar Petrov; Philip Torr 001; Adel Bibi (ICLR, 2024)

Continual Learning on a Diet: Learning from Sparsely Labeled Streams Under Constrained Computation. - Wenxuan Zhang 001; Youssef Mohamed; Bernard Ghanem; Philip Torr 001; Adel Bibi; Mohamed Elhoseiny (ICLR, 2024)

Efficient Error Certification for Physics-Informed Neural Networks. - Francisco Eiras; Adel Bibi; Rudy Bunel; Krishnamurthy Dj Dvijotham; Philip Torr 001; M. Pawan Kumar (ICML, 2024)

Position: Near to Mid-term Risks and Opportunities of Open-Source Generative AI. - Francisco Eiras; Aleksandar Petrov; Bertie Vidgen; Christian Schröder de Witt; Fabio Pizzati; Katherine Elkins; Supratik Mukhopadhyay; Adel Bibi; Botos Csaba; Fabro Steibel; Fazl Barez; Genevieve Smith; et al. (ICML, 2024)

Prompting a Pretrained Transformer Can Be a Universal Approximator. - Aleksandar Petrov; Philip Torr 001; Adel Bibi (ICML, 2024)

Towards Interpretable Deep Local Learning with Successive Gradient Reconciliation. - Yibo Yang; Xiaojie Li; Motasem Alfarra; Hasan Abed Al Kader Hammoud; Adel Bibi; Philip Torr 001; Bernard Ghanem (ICML, 2024)

FedMedICL: Towards Holistic Evaluation of Distribution Shifts in Federated Medical Imaging. - Kumail Alhamoud; Yasir Ghunaim; Motasem Alfarra; Thomas Hartvigsen; Philip Torr 001; Bernard Ghanem; Adel Bibi; Marzyeh Ghassemi (MICCAI (10), 2024)

Label Delay in Online Continual Learning. - Botos Csaba; Wenxuan Zhang 001; Matthias Müller 011; Ser Nam Lim; Philip Torr 001; Adel Bibi (NeurIPS, 2024)

Universal In-Context Approximation By Prompting Fully Recurrent Models. - Aleksandar Petrov; Tom A. Lamb; Alasdair Paren; Philip Torr 001; Adel Bibi (NeurIPS, 2024)

Efficient Lifelong Model Evaluation in an Era of Rapid Progress. - Ameya Prabhu; Vishaal Udandarao; Philip Torr 001; Matthias Bethge; Adel Bibi; Samuel Albanie (NeurIPS, 2024)

No "Zero-Shot" Without Exponential Data: Pretraining Concept Frequency Determines Multimodal Model Performance. - Vishaal Udandarao; Ameya Prabhu; Adhiraj Ghosh; Yash Sharma 001; Philip Torr 001; Adel Bibi; Samuel Albanie; Matthias Bethge (NeurIPS, 2024)

Can Large Language Model Agents Simulate Human Trust Behavior? - Chengxing Xie; Canyu Chen; Feiran Jia; Ziyu Ye; Shiyang Lai; Kai Shu; Jindong Gu; Adel Bibi; Ziniu Hu; David Jurgens; James Evans; Philip Torr 001; et al. (NeurIPS, 2024)

SynthCLIP: Are We Ready for a Fully Synthetic CLIP Training? - Hasan Abed Al Kader Hammoud; Hani Itani; Fabio Pizzati; Philip Torr 001; Adel Bibi; Bernard Ghanem (CoRR, 2024)

Can Large Language Model Agents Simulate Human Trust Behaviors? - Chengxing Xie; Canyu Chen; Feiran Jia; Ziyu Ye; Kai Shu; Adel Bibi; Ziniu Hu; Philip Torr 001; Bernard Ghanem; Guohao Li 001 (CoRR, 2024)

Lifelong Benchmarks: Efficient Model Evaluation in an Era of Rapid Progress. - Ameya Prabhu; Vishaal Udandarao; Philip Torr 001; Matthias Bethge; Adel Bibi; Samuel Albanie (CoRR, 2024)

Near to Mid-term Risks and Opportunities of Open Source Generative AI. - Francisco Eiras; Aleksandar Petrov; Bertie Vidgen; Christian Schröder de Witt; Fabio Pizzati; Katherine Elkins; Supratik Mukhopadhyay; Adel Bibi; Botos Csaba; Fabro Steibel; Fazl Barez; Genevieve Smith; et al. (CoRR, 2024)

Risks and Opportunities of Open-Source Generative AI. - Francisco Eiras; Aleksandar Petrov; Bertie Vidgen; Christian Schröder de Witt; Fabio Pizzati; Katherine Elkins; Supratik Mukhopadhyay; Adel Bibi; Aaron Purewal; Botos Csaba; Fabro Steibel; Fazel Keshtkar; et al. (CoRR, 2024)

Mimicking User Data: On Mitigating Fine-Tuning Risks in Closed Large Language Models. - Francisco Eiras; Aleksandar Petrov; Philip H. S. Torr; M. Pawan Kumar; Adel Bibi (CoRR, 2024)

Detecting LLM Hallucination Through Layer-wise Information Deficiency: Analysis of Unanswerable Questions and Ambiguous Prompts. - Hazel Kim; Adel Bibi; Philip Torr 001; Yarin Gal (CoRR, 2024)

Bi-Factorial Preference Optimization: Balancing Safety-Helpfulness in Language Models. - Wenxuan Zhang 001; Philip Torr 001; Mohamed Elhoseiny; Adel Bibi (ICLR, 2025)

Do as I do (Safely): Mitigating Task-Specific Fine-tuning Risks in Large Language Models. - Francisco Eiras; Aleksandar Petrov; Philip Torr 001; M. Pawan Kumar; Adel Bibi (ICLR, 2025)

Shh, don't say that! Domain Certification in LLMs. - Cornelius Emde; Alasdair Paren; Preetham Arvind; Maxime Guillaume Kayser; Tom Rainforth; Thomas Lukasiewicz; Philip Torr 001; Adel Bibi (ICLR, 2025)

Towards Certification of Uncertainty Calibration under Adversarial Attacks. - Cornelius Emde; Francesco Pinto; Thomas Lukasiewicz; Philip Torr 001; Adel Bibi (ICLR, 2025)

Open Problems in Machine Unlearning for AI Safety. - Fazl Barez; Tingchen Fu; Ameya Prabhu; Stephen Casper; Amartya Sanyal; Adel Bibi; Aidan O'Gara; Robert Kirk; Ben Bucknall; Timothy Fist; Luke Ong; Philip Torr 001; et al. (CoRR, 2025)

On the Coexistence and Ensembling of Watermarks. - Aleksandar Petrov; Shruti Agarwal; Philip H. S. Torr; Adel Bibi; John P. Collomosse (CoRR, 2025)

Shh, don't say that! Domain Certification in LLMs. - Cornelius Emde; Alasdair Paren; Preetham Arvind; Maxime Kayser; Tom Rainforth; Thomas Lukasiewicz; Bernard Ghanem; Philip H. S. Torr; Adel Bibi (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)

Attacking Multimodal OS Agents with Malicious Image Patches. - Lukas Aichberger; Alasdair Paren; Yarin Gal; Philip Torr 001; Adel Bibi (CoRR, 2025)

Rethinking Safety in LLM Fine-tuning: An Optimization Perspective. - Minseon Kim; Jin Myung Kwak; Lama Alssum; Bernard Ghanem; Philip Torr 001; David Krueger 001; Fazl Barez; Adel Bibi (CoRR, 2025)