Timothy Hospedales

papers

1,224

total citations

papers (21)

Learning to Generate Novel Domains for Domain Generalization

ECCV 2020arXiv

524

citations

Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

ICML 2024arXiv

123

citations

A Stochastic Approach to Bi-Level Optimization for Hyperparameter Optimization and Meta Learning

AAAI 2025arXiv

citations

Quality Diversity for Visual Pre-Training

ICCV 2023

citations

An Erudite Fine-Grained Visual Classification Model

CVPR 2023

citations

On-the-Fly Category Discovery

CVPR 2023

citations

FedL2P: Federated Learning to Personalize

NEURIPS 2023arXiv

citations

BayesTune: Bayesian Sparse Deep Model Fine-tuning

NEURIPS 2023

citations

Task-aware Adaptive Learning for Cross-domain Few-shot Learning

ICCV 2023

citations

Timothy Hospedales

papers (21)

Learning to Generate Novel Domains for Domain Generalization

Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

DADA: Differentiable Automatic Data Augmentation

Online Meta-Learning for Multi-Source and Semi-Supervised Domain Adaptation

DemoFusion: Democratising High-Resolution Image Generation With No $$$

BézierSketch: A generative model for scalable vector sketches

Online Meta-Critic Learning for Off-Policy Actor-Critic Methods

Zero-Shot Everything Sketch-Based Image Retrieval, and in Explainable Style

Fool Your (Vision and) Language Model with Embarrassingly Simple Permutations

EvoGrad: Efficient Gradient-Based Meta-Learning and Hyperparameter Optimization

SketchINR: A First Look into Sketches as Implicit Neural Representations

Recurrent Early Exits for Federated Learning with Heterogeneous Clients

Meta Omnium: A Benchmark for General-Purpose Learning-To-Learn

FW-Merging: Scaling Model Merging with Frank-Wolfe Optimization

A Stochastic Approach to Bi-Level Optimization for Hyperparameter Optimization and Meta Learning

Quality Diversity for Visual Pre-Training

An Erudite Fine-Grained Visual Classification Model

On-the-Fly Category Discovery

FedL2P: Federated Learning to Personalize

BayesTune: Bayesian Sparse Deep Model Fine-tuning

Task-aware Adaptive Learning for Cross-domain Few-shot Learning

papers (21)

Learning to Generate Novel Domains for Domain Generalization

Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

DADA: Differentiable Automatic Data Augmentation

Online Meta-Learning for Multi-Source and Semi-Supervised Domain Adaptation

DemoFusion: Democratising High-Resolution Image Generation With No $$$

BézierSketch: A generative model for scalable vector sketches

Online Meta-Critic Learning for Off-Policy Actor-Critic Methods

Zero-Shot Everything Sketch-Based Image Retrieval, and in Explainable Style

Fool Your (Vision and) Language Model with Embarrassingly Simple Permutations

EvoGrad: Efficient Gradient-Based Meta-Learning and Hyperparameter Optimization

SketchINR: A First Look into Sketches as Implicit Neural Representations

Recurrent Early Exits for Federated Learning with Heterogeneous Clients

Meta Omnium: A Benchmark for General-Purpose Learning-To-Learn

FW-Merging: Scaling Model Merging with Frank-Wolfe Optimization

A Stochastic Approach to Bi-Level Optimization for Hyperparameter Optimization and Meta Learning

Quality Diversity for Visual Pre-Training

An Erudite Fine-Grained Visual Classification Model

On-the-Fly Category Discovery

FedL2P: Federated Learning to Personalize

BayesTune: Bayesian Sparse Deep Model Fine-tuning

Task-aware Adaptive Learning for Cross-domain Few-shot Learning