PhysicsGen: Can Generative Models Learn from Images to Predict Complex Physical Relations?
Paper
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2503.05333
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Published
•
8
Janis Keuper
jkHSO
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authored
a paper
24 days ago
Watch your Up-Convolution: CNN Based Generative Deep Neural Networks are
Failing to Reproduce Spectral Distributions
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Detecting Images Generated by Deep Diffusion Models using their Local
Intrinsic Dimensionality
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jkHSO's activity
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papers
24 days ago
Watch your Up-Convolution: CNN Based Generative Deep Neural Networks are Failing to Reproduce Spectral Distributions
Paper
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2003.01826
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Published
Detecting Images Generated by Deep Diffusion Models using their Local Intrinsic Dimensionality
Paper
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2307.02347
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Published
How Do Training Methods Influence the Utilization of Vision Models?
Paper
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2410.14470
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Published
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5
WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images
Paper
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2411.11738
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Published
Can Biases in ImageNet Models Explain Generalization?
Paper
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2404.01509
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Published
Are Vision Language Models Texture or Shape Biased and Can We Steer Them?
Paper
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2403.09193
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Published
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9
On the Interplay of Convolutional Padding and Adversarial Robustness
Paper
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2308.06612
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Published
An Extended Study of Human-like Behavior under Adversarial Training
Paper
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2303.12669
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Published
The Power of Linear Combinations: Learning with Random Convolutions
Paper
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2301.11360
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Published
Does Medical Imaging learn different Convolution Filters?
Paper
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2210.13799
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Published
Robust Models are less Over-Confident
Paper
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2210.05938
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Published
Adversarial Robustness through the Lens of Convolutional Filters
Paper
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2204.02481
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Published
CNN Filter DB: An Empirical Investigation of Trained Convolutional Filters
Paper
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2203.15331
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Published
PhysicsGen: Can Generative Models Learn from Images to Predict Complex Physical Relations?
Paper
•
2503.05333
•
Published
•
8