影响力指数
论文质量、代表作、近期表现、广度与样本量置信度综合计算
68.07/100
前 3%
全站排名 #1,902
发表论文14 篇
平均评分
年均产出7.0 篇/年
Mark Niklas Mueller
研究方向
Large Language Models · ML for Code · deep learning · adversarial robustness · provable training
12
Certification for Differentially Private Prediction in Gradient-Based Training
ICML 2025Poster
14
Certified Robustness to Data Poisoning in Gradient-Based Training
ICLR 2025Rejected
二作13
Average Certified Radius is a Poor Metric for Randomized Smoothing
ICML 2025Poster
三作11
Automated Benchmark Generation for Repository-Level Coding Tasks
ICML 2025Poster
二作13
Average Certified Radius is a Poor Metric for Randomized Smoothing
ICLR 2025Rejected
三作14
Evading Data Contamination Detection for Language Models is (too) Easy
ICLR 2025Rejected
二作16
Gaussian Loss Smoothing Enables Certified Training with Tight Convex Relaxations
ICLR 2025Rejected
二作9
DAGER: Exact Gradient Inversion for Large Language Models
NeurIPS 2024Poster
19
Expressivity of ReLU-Networks under Convex Relaxations
ICLR 2024Poster
二作12
SPEAR: Exact Gradient Inversion of Batches in Federated Learning
NeurIPS 2024Poster
三作16
ConStat: Performance-Based Contamination Detection in Large Language Models
NeurIPS 2024Poster
二作20
Prompt Sketching for Large Language Models
ICLR 2024Rejected
二作22
Understanding Certified Training with Interval Bound Propagation
ICLR 2024Poster
二作23
SWT-Bench: Testing and Validating Real-World Bug-Fixes with Code Agents
NeurIPS 2024Poster
二作