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Asja Fischer

29 papers · 2013–2025 · 14 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (12) πŸ—ΊοΈ Taxonomy Completionist (10) 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (13) 🌈 Renaissance Researcher (8) 🧭 Keyword Pioneer πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (14) πŸ—ƒοΈ Keyword Collector (110) ⚑ Prolific Year (6) πŸš€ Conference Pioneer πŸ’Ž Century Club (29) πŸ”₯ Unstoppable (10) ❓ The Questioner

Conferences

ICML (7) AISTATS (4) ICLR (4) CVPR (2) EMNLP (2) WACV (2) ACL (1) CONLL (1) IJCAI (1) IJCNLP (1) INTERSPEECH (1) JMLR (1) NIPS (1) UAI (1)

Top co-authors

Denis Lukovnikov (7) Simon Damm (4) Sina DΓ€ubener (4) Mike Laszkiewicz (4) Johannes Lederer (4) Christian Igel (3) Yoshua Bengio (3) Nicolas Ballas (2) Linara Adilova (2) StanisΕ‚aw Jastrzebski (2)

Research topics

Privacy (1)

Keywords

generative model (4) adversarial attack (3) semantic segmentation (2) variational autoencoder (2) evidence lower bound (2) restricted boltzmann machine (2) adversarial robustness (2) latent diffusion (2) image forensics (2) uncertainty quantification (2) variational inference (1) semantic parsing (1) sample complexity (1) model architecture (1) attention mechanism (1) approximate inference (1) model interpretability (1) sparse coding (1) few-shot learning (1) compositional generalization (1)

Papers

Black-Box Forgery Attacks on Semantic Watermarks for Diffusion Models CVPR 2025
AnomalyDINO: Boosting Patch-Based Few-Shot Anomaly Detection with DINOv2 WACV 2025
ELBO, regularized maximum likelihood, and their common one-sample approximation for training stochastic neural networks UAI 2025
Can LLMs Explain Themselves Counterfactually? EMNLP 2025
Layer-wise linear mode connectivity ICLR 2024
Learning Sparse Codes with Entropy-Based ELBOs AISTATS 2024
AEROBLADE: Training-Free Detection of Latent Diffusion Images Using Autoencoder Reconstruction Error CVPR 2024
Single-Model Attribution of Generative Models Through Final-Layer Inversion ICML 2024
Uncertainty-Weighted Loss Functions for Improved Adversarial Attacks on Semantic Segmentation WACV 2024
Information Plane Analysis for Dropout Neural Networks ICLR 2023
The ELBO of Variational Autoencoders Converges to a Sum of Entropies AISTATS 2023
How Sampling Impacts the Robustness of Stochastic Neural Networks NIPS 2022
Marginal Tail-Adaptive Normalizing Flows ICML 2022
Improving Breadth-Wise Backpropagation in Graph Neural Networks Helps Learning Long-Range Dependencies. ICML 2021
Thresholded Adaptive Validation: Tuning the Graphical Lasso for Graph Recovery AISTATS 2021
Detecting Compositionally Out-of-Distribution Examples in Semantic Parsing EMNLP 2021
Insertion-based Tree Decoding ACL 2021
Insertion-based Tree Decoding IJCNLP 2021
On the convergence of the Metropolis algorithm with fixed-order updates for multivariate binary probability distributions AISTATS 2021
Leveraging Frequency Analysis for Deep Fake Image Recognition ICML 2020
Algorithms for Estimating the Partition Function of Restricted Boltzmann Machines (Extended Abstract) IJCAI 2020
Detecting Adversarial Examples for Speech Recognition via Uncertainty Quantification INTERSPEECH 2020
On the Relation Between the Sharpest Directions of DNN Loss and the SGD Step Length ICLR 2019
Improving Response Selection in Multi-Turn Dialogue Systems by Incorporating Domain Knowledge CONLL 2018
On the regularization of Wasserstein GANs ICLR 2018
A Closer Look at Memorization in Deep Networks ICML 2017
How to Center Deep Boltzmann Machines JMLR 2016
Bidirectional Helmholtz Machines ICML 2016
Approximation properties of DBNs with binary hidden units and real-valued visible units ICML 2013