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Aleksandar Bojchevski

26 papers · 2018–2026 · 7 venues · across top CS/AI venues

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

Achievements

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+10 more ↓ 🗺️ Taxonomy Completionist (42) 🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Sprint 🌉 Interdisciplinary Bridge · Bronze 🐣 Hot Topic Early Bird
👑 Triple Crown 🏆 Grand Slam 🤝 Dynamic Duo (15) 🔬 Deep Specialist (15) 🚀 Conference Pioneer 🔥 Unstoppable · Bronze 💎 Century Club · Bronze ❓ The Questioner (2) 🗃️ Keyword Collector (99) ⚡ Prolific Year · Productive

Venues

ICLR (9) NeurIPS (7) ICML (5) AISTATS (2) AAAI (1) EMNLP (1) UAI (1)

Top co-authors

Stephan Günnemann (15) Jan Schuchardt (5) Soroush H. Zargarbashi (5) Mohammad Sadegh Akhondzadeh (4) Simon Geisler (4) Johannes Gasteiger (3) Vijay Lingam (3) Yihan Wu (2) Daniel Zügner (2) Yan Scholten (2)

Research topics

Machine Learning (24) Deep Learning (20) Architectures (16) Learning Types · Machine Learning (12) Artificial Intelligence (11) Core AI (11) Core Methods (11) Optimization & Theory · Machine Learning (10) Learning Types · Deep Learning (4) Application Areas (3) Models (2) Optimization & Theory · Deep Learning (2) Techniques (2) Mathematics & Optimization (1) Bayesian & Probabilistic (1)

Keywords

graph neural network (13) adversarial robustness (9) node classification (6) randomized smoothing (5) conformal prediction (5) adversarial attack (5) robustness certificate (3) prediction set (3) message passing (3) collective robustness (2) neural network (2) certified robustness (2) inductive learning (2) graph perturbation (2) link prediction (2) random walk (2) transductive learning (1) robustness (1) representation learning (1) post-training quantization (1)

Papers

Optimal Conformal Prediction under Epistemic Uncertainty UAI 2026 KurTail : Kurtosis-based LLM Quantization EMNLP 2025 Robust Conformal Prediction with a Single Binary Certificate ICLR 2025 Conformal Inductive Graph Neural Networks ICLR 2024 Rethinking Label Poisoning for GNNs: Pitfalls and Attacks ICLR 2024 Robust Yet Efficient Conformal Prediction Sets ICML 2024 SVFT: Parameter-Efficient Fine-Tuning with Singular Vectors NeurIPS 2024 Adversarial Weight Perturbation Improves Generalization in Graph Neural Networks AAAI 2023 Are GATs Out of Balance? NeurIPS 2023 Conformal Prediction Sets for Graph Neural Networks ICML 2023 Hierarchical Randomized Smoothing NeurIPS 2023 Localized Randomized Smoothing for Collective Robustness Certification ICLR 2023 Probing Graph Representations AISTATS 2023 Unveiling the sampling density in non-uniform geometric graphs ICLR 2023 Are Defenses for Graph Neural Networks Robust? NeurIPS 2022 Generalization of Neural Combinatorial Solvers Through the Lens of Adversarial Robustness ICLR 2022 Randomized Message-Interception Smoothing: Gray-box Certificates for Graph Neural Networks NeurIPS 2022 Collective Robustness Certificates: Exploiting Interdependence in Graph Neural Networks ICLR 2021 Completing the Picture: Randomized Smoothing Suffers from the Curse of Dimensionality for a Large Family of Distributions AISTATS 2021 Robustness of Graph Neural Networks at Scale NeurIPS 2021 Efficient Robustness Certificates for Discrete Data: Sparsity-Aware Randomized Smoothing for Graphs, Images and More ICML 2020 Adversarial Attacks on Node Embeddings via Graph Poisoning ICML 2019 Certifiable Robustness to Graph Perturbations NeurIPS 2019 Predict then Propagate: Graph Neural Networks meet Personalized PageRank ICLR 2019 Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking ICLR 2018 NetGAN: Generating Graphs via Random Walks ICML 2018