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Schott, Lukas

  1. Comparative Study of Deep Learning Software Frameworks
    2015/11/19 by Soheil Bahrampour, Naveen Ramakrishnan, Bahrampour, Soheil +5 · 2 voices
    #cs.LG
  2. Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse\n Coding
    2020/07/21 by David Klindt, Klindt, David, Lukas Schott +11 · 12 citations
    Computer Science · #Computer Vision and Pattern Recognition (cs.CV) #Digital Media Forensic Detection #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Image and Signal Denoising Methods #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  3. Towards the first adversarially robust neural network model on MNIST
    2018/05/23 by Schott, Lukas, Rauber, Jonas, Bethge, Matthias +1 · 3 citations
    #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences
  4. Score-Based Generative Classifiers
    2021/10/01 by Zimmermann, Roland S., Schott, Lukas, Song, Yang +2 · 3 citations
    #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  5. Learned Watershed: End-to-End Learning of Seeded Segmentation
    2017/04/07 by Wolf, Steffen, Schott, Lukas, Köthe, Ullrich +1 · 1 citation
    #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences
  6. Visual Representation Learning Does Not Generalize Strongly Within the Same Domain
    2021/07/17 by Schott, Lukas, von Kügelgen, Julius, Träuble, Frederik +6 · 1 citation
    #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  7. Understanding Neural Coding on Latent Manifolds by Sharing Features and Dividing Ensembles
    2022/10/06 by Martin Bjerke, Bjerke, Martin, Lukas Schott +9 · 1 citation
    Biochemistry, Genetics and Molecular Biology · Computer Science · Neuroscience · #Cell Image Analysis Techniques #FOS: Biological sciences #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural dynamics and brain function #Neurons and Cognition (q-bio.NC)
  8. Mind the Gap Between Synthetic and Real: Utilizing Transfer Learning to Probe the Boundaries of Stable Diffusion Generated Data
    2024/05/06 by Leonhard Hennicke, Hennicke, Leonhard, C. Adriano +7 · 1 citation
    Computer Science · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Neural Networks and Applications
  9. Attention Is All You Need For Mixture-of-Depths Routing
    2024/12/30 by Advait Gadhikar, Gadhikar, Advait, Majumdar, Souptik Kumar +8 · 1 citation
    Engineering · #Manufacturing Process and Optimization #VLSI and FPGA Design Techniques #Optimization and Packing Problems
  10. Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation
    2025/06/02 by Niclas Popp, Kevin Alexander Laube, Popp, Niclas +5 · 1 citation
    Computer Science · #Advanced Neural Network Applications #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #cs.CV