Carola-Bibiane Schönlieb
28 papers · 2018–2026 · 10 conferences · across top CS/AI conferences
Achievements
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🌍 Conference Polyglot (10) 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🏃 Academic Marathon (7)
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Hot Topic Early Bird
🌉
Interdisciplinary Bridge
🌍
Conference Polyglot
(10)
🧬
Topic Evolution
🏆
Grand Slam
🏆
Keyword Champion
(2)
🗃️
Keyword Collector
(88)
🚀
Conference Pioneer
💎
Century Club
(27)
🔥
Unstoppable
(8)
⚡
Prolific Year
(7)
Conferences
ICML (7)
AAAI (4)
NIPS (4)
JMLR (3)
MICCAI (3)
CVPR (2)
ICLR (2)
ECCV (1)
ICCV (1)
WACV (1)
Top co-authors
Keywords
image restoration
(4)
graph neural network
(4)
inverse problem
(4)
representation learning
(2)
stochastic gradient descent
(2)
compressed sensing
(2)
diffeomorphic transformation
(2)
deep reinforcement learning
(2)
message passing
(2)
proximal algorithm
(2)
non-convex optimization
(1)
self-attention mechanism
(1)
few-shot learning
(1)
variational inference
(1)
contrastive learning
(1)
feature learning
(1)
cross-modal learning
(1)
multi-task learning
(1)
prompt engineering
(1)
batch normalization
(1)
Papers
Blessing of Dimensionality for Approximating Sobolev Classes on Manifolds
AAAI 2026
Estimation of single-cell and tissue perturbation effect in spatial transcriptomics via Spatial Causal Disentanglement
ICLR 2025
Score-based Pullback Riemannian Geometry: Extracting the Data Manifold Geometry using Anisotropic Flows
ICML 2025
Cross-Modal Few-Shot Learning with Second-Order Neural Ordinary Differential Equations
AAAI 2025
Learning Regularization for Graph Inverse Problems
AAAI 2025
On Oversquashing in Graph Neural Networks Through the Lens of Dynamical Systems
AAAI 2025
Implicit U-KAN2.0: Dynamic, Efficient and Interpretable Medical Image Segmentation
MICCAI 2025
DiTASK: Multi-Task Fine-Tuning with Diffeomorphic Transformations
CVPR 2025
G-Adaptivity: optimised graph-based mesh relocation for finite element methods
ICML 2025
Lie Algebra Canonicalization: Equivariant Neural Operators under arbitrary Lie Groups
ICLR 2025
Graph Adaptive Autoregressive Moving Average Models
ICML 2025
HAMLET: Graph Transformer Neural Operator for Partial Differential Equations
ICML 2024
DiGRAF: Diffeomorphic Graph-Adaptive Activation Function
NIPS 2024
GRANOLA: Adaptive Normalization for Graph Neural Networks
NIPS 2024
Weakly Convex Regularisers for Inverse Problems: Convergence of Critical Points and Primal-Dual Optimisation
ICML 2024
Diffusion Models Encode the Intrinsic Dimension of Data Manifolds
ICML 2024
Biophysics Informed Pathological Regularisation for Brain Tumour Segmentation
MICCAI 2024
Spatiotemporal Graph Neural Network Modelling Perfusion MRI
MICCAI 2024
A Continuous-time Stochastic Gradient Descent Method for Continuous Data
JMLR 2023
SCOTCH and SODA: A Transformer Video Shadow Detection Framework
CVPR 2023
TFPnP: Tuning-free Plug-and-Play Proximal Algorithms with Applications to Inverse Imaging Problems
JMLR 2022
HERS Superpixels: Deep Affinity Learning for Hierarchical Entropy Rate Segmentation
WACV 2022
On Biased Stochastic Gradient Estimation
JMLR 2022
Rethinking Video Rain Streak Removal: A New Synthesis Model and a Deraining Network with Video Rain Prior
ECCV 2022
End-to-end reconstruction meets data-driven regularization for inverse problems
NIPS 2021
Tuning-free Plug-and-Play Proximal Algorithm for Inverse Imaging Problems
ICML 2020
RainFlow: Optical Flow Under Rain Streaks and Rain Veiling Effect
ICCV 2019
Adversarial Regularizers in Inverse Problems
NIPS 2018