Sophie Langer

13 papers Journal 13
YearRankTypeTitle / Venue / Authors
2026 J jnl
Latent Structure Emergence in Diffusion Models via Confidence-Based Filtering.
CoRR
Wei Wei, Yizhou Zeng, Kuntian Chen, Sophie Langer, Mariia Seleznova, Hung-Hsu Chou
2025 J jnl
Learning Green's function efficiently using low-rank approximations.
Mach. Learn.
Kishan Wimalawarne, Taiji Suzuki, Sophie Langer
2025 J jnl
On the expressivity of deep Heaviside networks.
CoRR
Insung Kong, Juntong Chen, Sophie Langer, Johannes Schmidt-Hieber
2025 J jnl
Training Diagonal Linear Networks with Stochastic Sharpness-Aware Minimization.
CoRR
Gabriel Clara, Sophie Langer, Johannes Schmidt-Hieber
2024 J jnl
Dropout Regularization Versus l2-Penalization in the Linear Model.
J. Mach. Learn. Res.
Gabriel Clara, Sophie Langer, Johannes Schmidt-Hieber
2024 J jnl
On the VC dimension of deep group convolutional neural networks.
CoRR
Anna Sepliarskaia, Sophie Langer, Johannes Schmidt-Hieber
2023 J jnl
Learning Green's Function Efficiently Using Low-Rank Approximations.
CoRR
Kishan Wimalawarne, Taiji Suzuki, Sophie Langer
2022 J jnl
Estimation of a Function of Low Local Dimensionality by Deep Neural Networks.
IEEE Trans. Inf. Theory
Michael Kohler, Adam Krzyzak, Sophie Langer
2021 J jnl
Analysis of the rate of convergence of fully connected deep neural network regression estimates with smooth activation function.
J. Multivar. Anal.
Sophie Langer
2021 J jnl
Approximating smooth functions by deep neural networks with sigmoid activation function.
J. Multivar. Anal.
Sophie Langer
2020 J jnl
Approximating smooth functions by deep neural networks with sigmoid activation function.
CoRR
Sophie Langer
2019 J jnl
Deep Learning and MARS: A Connection.
CoRR
Michael Kohler, Adam Krzyzak, Sophie Langer
2019 J jnl
On the rate of convergence of fully connected very deep neural network regression estimates.
CoRR
Michael Kohler, Sophie Langer