Timothy Hospedales
66 papers · 2015–2026 · 15 conferences · across top CS/AI conferences
Achievements
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(15)
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Keyword Collector
(180)
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Century Club
(65)
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Trend Setter
Conferences
ICLR (17)
ICML (9)
CVPR (7)
NIPS (7)
AAAI (5)
ECCV (5)
EMNLP (4)
ICCV (3)
WACV (3)
ACML (1)
AUTOML (1)
IJCNLP (1)
JMLR (1)
L4DC (1)
MIDL (1)
Top co-authors
Keywords
domain adaptation
(4)
few-shot learning
(3)
hyperparameter optimization
(3)
domain generalization
(3)
link prediction
(3)
federated learning
(3)
transfer learning
(3)
bayesian inference
(3)
edge computing
(2)
zero-shot learning
(2)
parameter-efficient fine-tuning
(2)
model compression
(2)
tucker decomposition
(2)
bi-level optimization
(2)
reinforcement learning
(2)
image generation
(2)
unsupervised learning
(2)
representation learning
(2)
tensor factorization
(2)
stochastic neural network
(2)
Papers
FedP²EFT: Federated Learning to Personalize PEFT for Multilingual LLMs
AAAI 2026
HyperIV: Real-time Implied Volatility Smoothing
ICML 2025
VL-ICL Bench: The Devil in the Details of Multimodal In-Context Learning
ICLR 2025
FW-Merging: Scaling Model Merging with Frank-Wolfe Optimization
ICCV 2025
MemControl: Mitigating Memorization in Diffusion Models via Automated Parameter Selection
WACV 2025
A Stochastic Approach to Bi-Level Optimization for Hyperparameter Optimization and Meta Learning
AAAI 2025
ConceptPrune: Concept Editing in Diffusion Models via Skilled Neuron Pruning
ICLR 2025
LiFT: Learning to Fine-Tune via Bayesian Parameter Efficient Meta Fine-Tuning
ICLR 2025
FedHB: Hierarchical Bayesian Federated Learning
JMLR 2025
A Bayesian Approach to Data Point Selection
NIPS 2024
Fool Your (Vision and) Language Model with Embarrassingly Simple Permutations
ICML 2024
SketchINR: A First Look into Sketches as Implicit Neural Representations
CVPR 2024
Neural Fine-Tuning Search for Few-Shot Learning
ICLR 2024
Meta-Learned Kernel for Blind Super-Resolution Kernel Estimation
WACV 2024
A Hierarchical Bayesian Model for Few-Shot Meta Learning
ICLR 2024
DemoFusion: Democratising High-Resolution Image Generation With No $$$
CVPR 2024
Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models
ICML 2024
Recurrent Early Exits for Federated Learning with Heterogeneous Clients
ICML 2024
Parameter-Efficient Fine-Tuning for Medical Image Analysis: The Missed Opportunity
MIDL 2024
MobileQuant: Mobile-friendly Quantization for On-device Language Models
EMNLP 2024
FairTune: Optimizing Parameter Efficient Fine Tuning for Fairness in Medical Image Analysis
ICLR 2024
Feed-Forward Latent Domain Adaptation
WACV 2024
Learning where and when to reason in neuro-symbolic inference
ICLR 2023
Better Practices for Domain Adaptation
AUTOML 2023
FedL2P: Federated Learning to Personalize
NIPS 2023
Zero-Shot Everything Sketch-Based Image Retrieval, and in Explainable Style
CVPR 2023
An Erudite Fine-Grained Visual Classification Model
CVPR 2023
Meta Omnium: A Benchmark for General-Purpose Learning-To-Learn
CVPR 2023
On-the-Fly Category Discovery
CVPR 2023
Quality Diversity for Visual Pre-Training
ICCV 2023
Task-aware Adaptive Learning for Cross-domain Few-shot Learning
ICCV 2023
BayesTune: Bayesian Sparse Deep Model Fine-tuning
NIPS 2023
Amortised Invariance Learning for Contrastive Self-Supervision
ICLR 2023
Domain Generalisation via Domain Adaptation: An Adversarial Fourier Amplitude Approach
ICLR 2023
ChiroDiff: Modelling chirographic data with Diffusion Models
ICLR 2023
MEDFAIR: Benchmarking Fairness for Medical Imaging
ICLR 2023
SketchODE: Learning neural sketch representation in continuous time
ICLR 2022
Fisher SAM: Information Geometry and Sharpness Aware Minimisation
ICML 2022
Loss Function Learning for Domain Generalization by Implicit Gradient
ICML 2022
Vision-based System Identification and 3D Keypoint Discovery using Dynamics Constraints
L4DC 2022
Online Hyperparameter Meta-Learning with Hypergradient Distillation
ICLR 2022
Visual Representation Learning over Latent Domains
ICLR 2022
Distance-Based Regularisation of Deep Networks for Fine-Tuning
ICLR 2021
EvoGrad: Efficient Gradient-Based Meta-Learning and Hyperparameter Optimization
NIPS 2021
Simple and Effective Stochastic Neural Networks
AAAI 2021
Neural-Symbolic Integration: A Compositional Perspective
AAAI 2021
Robust Domain Randomised Reinforcement Learning through Peer-to-Peer Distillation
ACML 2021
Interpreting Knowledge Graph Relation Representation from Word Embeddings
ICLR 2021
Weight-covariance alignment for adversarially robust neural networks
ICML 2021
BézierSketch: A generative model for scalable vector sketches
ECCV 2020
DADA: Differentiable Automatic Data Augmentation
ECCV 2020
Physics-as-Inverse-Graphics: Unsupervised Physical Parameter Estimation from Video
ICLR 2020
Learning to Generate Novel Domains for Domain Generalization
ECCV 2020
Online Meta-Learning for Multi-Source and Semi-Supervised Domain Adaptation
ECCV 2020
Online Meta-Critic Learning for Off-Policy Actor-Critic Methods
NIPS 2020
Deep Domain-Adversarial Image Generation for Domain Generalisation
AAAI 2020
What the Vec? Towards Probabilistically Grounded Embeddings
NIPS 2019
Feature-Critic Networks for Heterogeneous Domain Generalization
ICML 2019
Multi-relational Poincaré Graph Embeddings
NIPS 2019
TuckER: Tensor Factorization for Knowledge Graph Completion
EMNLP 2019
TuckER: Tensor Factorization for Knowledge Graph Completion
IJCNLP 2019
Analogies Explained: Towards Understanding Word Embeddings
ICML 2019
Learning Unsupervised Word Translations Without Adversaries
EMNLP 2018
Deep Multi-Task Learning to Recognise Subtle Facial Expressions of Mental States
ECCV 2018
Gaussian Visual-Linguistic Embedding for Zero-Shot Recognition
EMNLP 2016
Making Better Use of Edges via Perceptual Grouping
CVPR 2015