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Luca Daniel

22 papers · 2018–2025 · 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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+12 more ↓ πŸ—ΊοΈ Taxonomy Completionist (44) 🌍 Conference Polyglot Β· Silver πŸƒ Academic Marathon Β· Sprint πŸŒ‰ Interdisciplinary Bridge Β· Bronze 🐣 Hot Topic Early Bird
πŸ”¬ Deep Specialist (11) πŸ† Grand Slam πŸ‘‘ Triple Crown πŸ† Keyword Champion (3) 🧭 Keyword Pioneer 🀝 Dynamic Duo (13) ⚑ Prolific Year Β· Productive πŸ”₯ Unstoppable Β· Bronze ❓ The Questioner πŸ’Ž Century Club Β· Bronze πŸš€ Conference Pioneer πŸ—ƒοΈ Keyword Collector (94)

Venues

ICML (8) AAAI (5) ICLR (3) NeurIPS (3) AISTATS (1) CVPR (1) ECCV (1)

Top co-authors

Pin-Yu Chen (13) Tsui-Wei Weng (8) Sijia Liu (8) Lily Weng (7) Ching-Yun Ko (7) Jeet Mohapatra (5) Akhilan Boopathy (4) Alexandre Megretski (3) Wang Zhang (3) Cho-jui Hsieh (3)

Research topics

Machine Learning (20) Artificial Intelligence (17) Core AI (16) Deep Learning (13) Learning Types Β· Machine Learning (12) Optimization & Theory Β· Machine Learning (10) Core Methods (6) Learning Types Β· Deep Learning (6) Optimization & Theory Β· Deep Learning (6) Techniques (4) Application Areas (3) Architectures (3) Natural Language Processing (1) Reinforcement Learning (1) Robotics (1)

Keywords

adversarial robustness (13) neural network verification (5) neural network (5) adversarial attack (4) neural network robustness (3) adversarial perturbation (3) neural network certification (3) randomized smoothing (3) robustness certificate (2) formal verification (2) contrastive learning (2) linear programming (2) certified robustness (2) adversarial defense (2) adversarial example (2) policy learning (1) robust classification (1) robust optimization (1) epistemic uncertainty (1) uncertainty quantification (1)

Papers

Large Language Models can Become Strong Self-Detoxifiers ICLR 2025 One Step Closer to Unbiased Aleatoric Uncertainty Estimation AAAI 2024 What Would Gauss Say About Representations? Probing Pretrained Image Models using Synthetic Gaussian Benchmarks ICML 2024 ConCerNet: A Contrastive Learning Based Framework for Automated Conservation Law Discovery and Trustworthy Dynamical System Prediction ICML 2023 Adversarially Robust Conformal Prediction ICLR 2022 Learning from Multiple Annotator Noisy Labels via Sample-Wise Label Fusion ECCV 2022 Revisiting Contrastive Learning through the Lens of Neighborhood Component Analysis: an Integrated Framework ICML 2022 Fast Training of Provably Robust Neural Networks by SingleProp AAAI 2021 Hidden Cost of Randomized Smoothing AISTATS 2021 Robust Deep Reinforcement Learning through Adversarial Loss NeurIPS 2021 Fastened CROWN: Tightened Neural Network Robustness Certificates AAAI 2020 Higher-Order Certification For Randomized Smoothing NeurIPS 2020 Neural Network Control Policy Verification With Persistent Adversarial Perturbation ICML 2020 Proper Network Interpretability Helps Adversarial Robustness in Classification ICML 2020 Towards Certificated Model Robustness Against Weight Perturbations AAAI 2020 Towards Verifying Robustness of Neural Networks Against A Family of Semantic Perturbations CVPR 2020 CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks AAAI 2019 POPQORN: Quantifying Robustness of Recurrent Neural Networks ICML 2019 PROVEN: Verifying Robustness of Neural Networks with a Probabilistic Approach ICML 2019 Efficient Neural Network Robustness Certification with General Activation Functions NeurIPS 2018 Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach ICLR 2018 Towards Fast Computation of Certified Robustness for ReLU Networks ICML 2018