← Authors

Bruno Ribeiro

27 papers · 2019–2025 · 10 conferences · across top CS/AI conferences

Achievements

🐝 Cross-Pollinator (12) 🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🌈 Renaissance Researcher (9) πŸ—ΊοΈ Taxonomy Completionist (46) 🌍 Conference Polyglot (10) πŸƒ Academic Marathon (6) πŸ‘‘ Triple Crown πŸ† Grand Slam 🧬 Topic Evolution πŸ’Ž Century Club (27) πŸ—ƒοΈ Keyword Collector (80) ⚑ Prolific Year (7) πŸ”₯ Unstoppable (7)

Conferences

ICLR (8) NIPS (6) ICML (5) UAI (2) AAAI (1) ACL (1) AISTATS (1) CVPR (1) EACL (1) EMNLP (1)

Top co-authors

Beatrice Bevilacqua (5) Balasubramaniam Srinivasan (3) Moshe Eliasof (3) S Chandra Mouli (3) Jure Leskovec (3) Jianfei Gao (2) Jincheng Zhou (2) Carola-Bibiane SchΓΆnlieb (2) Krishna Sri Ipsit Mantri (2) Joshua Robinson (2)

Keywords

graph neural network (8) representation learning (4) graph representation (3) graph classification (2) graph representation learning (2) out-of-distribution generalization (2) large language model (2) distribution shift (2) diffeomorphic transformation (2) vision transformer (1) named entity recognition (1) link prediction (1) inductive reasoning (1) causal reasoning (1) zero-shot learning (1) markov chain monte carlo (1) sql generation (1) domain generalization (1) parameter efficient (1) permutation equivariance (1)

Papers

Zero-Shot Generalization of GNNs over Distinct Attribute Domains ICML 2025
Holographic Node Representations: Pre-training Task-Agnostic Node Embeddings ICLR 2025
Scalable Out-of-Distribution Robustness in the Presence of Unobserved Confounders AISTATS 2025
DiTASK: Multi-Task Fine-Tuning with Diffeomorphic Transformations CVPR 2025
Constraint-based Causal Discovery from a Collection of Conditioning Sets UAI 2025
Castle: Causal Cascade Updates in Relational Databases with Large Language Models EMNLP 2025
Efficient Subgraph GNNs by Learning Effective Selection Policies ICLR 2024
Vertical Validation: Evaluating Implicit Generative Models for Graphs on Thin Support Regions UAI 2024
DiGRAF: Diffeomorphic Graph-Adaptive Activation Function NIPS 2024
GraphMETRO: Mitigating Complex Graph Distribution Shifts via Mixture of Aligned Experts NIPS 2024
A Foundation Model for Zero-shot Logical Query Reasoning NIPS 2024
Unlocking the Potential of Large Language Models for Clinical Text Anonymization: A Comparative Study ACL 2024
MetaPhysiCa: Improving OOD Robustness in Physics-informed Machine Learning ICLR 2024
Effective passive membership inference attacks in federated learning against overparameterized models ICLR 2023
INCOGNITUS: A Toolbox for Automated Clinical Notes Anonymization EACL 2023
OOD Link Prediction Generalization Capabilities of Message-Passing GNNs in Larger Test Graphs NIPS 2022
On the Equivalence Between Temporal and Static Equivariant Graph Representations ICML 2022
Asymmetry Learning for Counterfactually-invariant Classification in OOD Tasks ICLR 2022
Size-Invariant Graph Representations for Graph Classification Extrapolations ICML 2021
Reconstruction for Powerful Graph Representations NIPS 2021
Neural Networks for Learning Counterfactual G-Invariances from Single Environments ICLR 2021
A Collective Learning Framework to Boost GNN Expressiveness for Node Classification ICML 2021
On the Equivalence between Positional Node Embeddings and Structural Graph Representations ICLR 2020
Infinity Learning: Learning Markov Chains from Aggregate Steady-State Observations AAAI 2020
Unsupervised Joint k-node Graph Representations with Compositional Energy-Based Models NIPS 2020
Relational Pooling for Graph Representations ICML 2019
Janossy Pooling: Learning Deep Permutation-Invariant Functions for Variable-Size Inputs ICLR 2019