Asja Fischer
29 papers · 2013–2026 · 13 venues · across top CS/AI venues
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Achievements
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🗺️ Taxonomy Completionist (54) 🏃 Academic Marathon · Half 🌍 Conference Polyglot · Gold 🌉 Interdisciplinary Bridge · Bronze 🐣 Hot Topic Early Bird
🧬
Topic Evolution
🗃️
Keyword Collector
(136)
🚀
Conference Pioneer
🔥
Unstoppable · Silver
❓
The Questioner
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Prolific Year · Productive
💎
Century Club · Bronze
🌈
Renaissance Researcher
(6)
Venues
Top co-authors
Research topics
Machine Learning
(21)
Optimization & Theory
(16)
Deep Learning
(15)
Models
(11)
Artificial Intelligence
(8)
Core AI
(7)
Learning Types
(7)
Core Methods
(6)
Computer Vision
(4)
Mathematics & Optimization
(3)
Analysis
(3)
Application Areas
(3)
Architectures
(3)
Bayesian & Probabilistic
(3)
Learning Paradigms
(3)
Keywords
generative model
(5)
adversarial attack
(3)
evidence lower bound
(3)
uncertainty quantification
(3)
image forensics
(2)
deepfake detection
(2)
out-of-distribution detection
(2)
variational inference
(2)
bayesian neural network
(2)
semantic segmentation
(2)
anomaly detection
(2)
adversarial robustness
(2)
generative adversarial network
(2)
neural network
(2)
restricted boltzmann machine
(2)
latent diffusion
(2)
variational autoencoder
(2)
attention mechanism
(1)
few-shot learning
(1)
sparse coding
(1)
Papers
ClusterMark: Towards Robust Watermarking for Autoregressive Image Generators with Visual Token Clustering
CVPR 2026
AnomalyDINO: Boosting Patch-Based Few-Shot Anomaly Detection with DINOv2
WACV 2025
Black-Box Forgery Attacks on Semantic Watermarks for Diffusion Models
CVPR 2025
Can LLMs Explain Themselves Counterfactually?
EMNLP 2025
ELBO, regularized maximum likelihood, and their common one-sample approximation for training stochastic neural networks
UAI 2025
AEROBLADE: Training-Free Detection of Latent Diffusion Images Using Autoencoder Reconstruction Error
CVPR 2024
Layer-wise linear mode connectivity
ICLR 2024
Learning Sparse Codes with Entropy-Based ELBOs
AISTATS 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
NeurIPS 2022
Marginal Tail-Adaptive Normalizing Flows
ICML 2022
Detecting Compositionally Out-of-Distribution Examples in Semantic Parsing
EMNLP 2021
Improving Breadth-Wise Backpropagation in Graph Neural Networks Helps Learning Long-Range Dependencies.
ICML 2021
Insertion-based Tree Decoding
ACL 2021
On the convergence of the Metropolis algorithm with fixed-order updates for multivariate binary probability distributions
AISTATS 2021
Thresholded Adaptive Validation: Tuning the Graphical Lasso for Graph Recovery
AISTATS 2021
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
Leveraging Frequency Analysis for Deep Fake Image Recognition
ICML 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
Bidirectional Helmholtz Machines
ICML 2016
How to Center Deep Boltzmann Machines
JMLR 2016
Approximation properties of DBNs with binary hidden units and real-valued visible units
ICML 2013