Pau Rodriguez
23 papers · 2018–2025 · 10 conferences · across top CS/AI conferences
Achievements
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π Academic Marathon (7) π Cross-Pollinator (12) π Conference Polyglot (10) π§ Keyword Pioneer π Renaissance Researcher (6)
π
Renaissance Researcher
(6)
π
Interdisciplinary Bridge
πΊοΈ
Taxonomy Completionist
(40)
π
Triple Crown
π€
Dynamic Duo
(12)
π
Conference Pioneer
π
Century Club
(23)
ποΈ
Keyword Collector
(83)
π₯
Unstoppable
(6)
β‘
Prolific Year
(7)
Conferences
NIPS (6)
ICML (3)
WACV (3)
CVPR (2)
ECCV (2)
ICCV (2)
ICLR (2)
ACL (1)
CLEAR (1)
JMLR (1)
Top co-authors
Keywords
self-supervised learning
(5)
representation learning
(2)
continual learning
(2)
image classification
(2)
transfer learning
(2)
catastrophic forgetting
(2)
adversarial robustness
(2)
contrastive learning
(2)
image restoration
(1)
domain adaptation
(1)
semantic segmentation
(1)
image generation
(1)
weakly supervised learning
(1)
anomaly detection
(1)
few-shot learning
(1)
medical imaging
(1)
multi-label learning
(1)
independent component analysis
(1)
neural network training
(1)
model-agnostic meta-learning
(1)
Papers
Controlling Language and Diffusion Models by Transporting Activations
ICLR 2025
Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity
ICML 2025
StarVector: Generating Scalable Vector Graphics Code from Images and Text
CVPR 2025
Whispering Experts: Neural Interventions for Toxicity Mitigation in Language Models
ICML 2024
Group Robust Classification Without Any Group Information
NIPS 2023
CADet: Fully Self-Supervised Out-Of-Distribution Detection With Contrastive Learning
NIPS 2023
DeepPCR: Parallelizing Sequential Operations in Neural Networks
NIPS 2023
OCR-VQGAN: Taming Text-Within-Image Generation
WACV 2023
The Role of Entropy and Reconstruction in Multi-View Self-Supervised Learning
ICML 2023
Constraining Representations Yields Models That Know What They Don't Know
ICLR 2023
GEO-Bench: Toward Foundation Models for Earth Monitoring
NIPS 2023
A Closer Look at Embedding Propagation for Manifold Smoothing
JMLR 2022
Data Augmentation for Intent Classification with Off-the-shelf Large Language Models
ACL 2022
Disentanglement via Mechanism Sparsity Regularization: A New Principle for Nonlinear ICA
CLEAR 2022
Multi-Label Iterated Learning for Image Classification With Label Ambiguity
CVPR 2022
Seasonal Contrast: Unsupervised Pre-Training From Uncurated Remote Sensing Data
ICCV 2021
Beyond Trivial Counterfactual Explanations With Diverse Valuable Explanations
ICCV 2021
Continual Learning via Local Module Composition
NIPS 2021
A Weakly Supervised Consistency-Based Learning Method for COVID-19 Segmentation in CT Images
WACV 2021
OverNet: Lightweight Multi-Scale Super-Resolution With Overscaling Network
WACV 2021
Embedding Propagation: Smoother Manifold for Few-Shot Classification
ECCV 2020
Online Fast Adaptation and Knowledge Accumulation (OSAKA): a New Approach to Continual Learning
NIPS 2020
Attend and Rectify: a gated attention mechanism for fine-grained recovery
ECCV 2018