Bruno Ribeiro
27 papers · 2019–2025 · 10 conferences · across top CS/AI conferences
Achievements
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π Academic Marathon (6) π Interdisciplinary Bridge π§ Keyword Pioneer π Conference Polyglot (10) π£ Hot Topic Early Bird
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(46)
π
Conference Polyglot
(10)
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Academic Marathon
(6)
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Triple Crown
π
Grand Slam
π§¬
Topic Evolution
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Century Club
(27)
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(80)
β‘
Prolific Year
(7)
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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
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