Publications


Showing entries 1 - 20 out of 134

Multi-window STFT phase retrieval: lattice uniqueness. / Liehr, Lukas; Grohs, Philipp; Rathmair, Martin.

In: Journal of Functional Analysis, 15.09.2024.

Publications: Contribution to journalArticlePeer Reviewed


Phase retrieval in Fock space and perturbation of Liouville sets. / Liehr, Lukas; Grohs, Philipp; Rathmair, Martin.

In: Revista Matematica Iberoamericana, 31.08.2024.

Publications: Contribution to journalArticlePeer Reviewed


Stable Gabor Phase Retrieval in Gaussian Shift-Invariant Spaces via Biorthogonality. / Liehr, Lukas; Grohs, Philipp.

In: Constructive Approximation, Vol. 59, No. 1, 02.2024, p. 61-111.

Publications: Contribution to journalArticlePeer Reviewed


Towards a transferable fermionic neural wavefunction for molecules. / Scherbela, Michael; Gerard, Leon; Grohs, Philipp.

In: Nature Communications, Vol. 15, No. 1, 120, 2024.

Publications: Contribution to journalArticlePeer Reviewed


FakET: Simulating Cryo-Electron Tomograms with Neural Style Transfer. / Harar, Pavol; Herrmann, Lukas; Grohs, Philipp et al.

2023.

Publications: Other publicationOther


Sobolev-type embeddings for neural network approximation spaces. / Grohs, Philipp; Voigtländer, Felix.

2. ed. 2023. p. 579-599.

Publications: Working paperPreprint


Non-uniqueness theory in sampled STFT phase retrieval. / Liehr, Lukas; Grohs, Philipp.

In: SIAM Journal on Mathematical Analysis, 21.03.2023.

Publications: Contribution to journalArticlePeer Reviewed


Phaseless sampling on square-root lattices. / Liehr, Lukas; Grohs, Philipp.

In: Foundations of Computational Mathematics, 08.02.2023.

Publications: Contribution to journalArticlePeer Reviewed


Phase Transitions in Rate Distortion Theory and Deep Learning. / Grohs, Philipp; Klotz, Andreas; Voigtlaender, Felix (Corresponding author).

In: Foundations of Computational Mathematics, Vol. 23, No. 1, 02.2023, p. 329-392.

Publications: Contribution to journalArticlePeer Reviewed


Injectivity of Gabor phase retrieval from lattice measurements. / Grohs, Philipp; Liehr, Lukas (Corresponding author).

In: Applied and Computational Harmonic Analysis, Vol. 62, 01.2023, p. 173-193.

Publications: Contribution to journalArticlePeer Reviewed


A proof that artificial neural networks overcome the curse of dimensionality in the numerical approximation of Black-Scholes partial differential equations. / Grohs, Philipp; Hornung, Fabian ; Jentzen, Arnulf et al.

In: Memoirs of the American Mathematical Society, Vol. 284, No. 1410, 2023.

Publications: Contribution to journalArticlePeer Reviewed


Arithmetic progressions and holomorphic phase retrieval. / Liehr, Lukas.

2023.

Publications: Working paperPreprint


Learning ReLU networks to high uniform accuracy is intractable. / Berner, Julius; Grohs, Philipp; Voigtlaender, Felix.

2023. Paper presented at The Eleventh International Conference on Learning Representations: ICLR 2023.

Publications: Contribution to conferencePaperPeer Reviewed


Phase retrieval in Fock space and perturbation of Liouville sets. / Liehr, Lukas; Grohs, Philipp; Rathmair, Martin.

2023.

Publications: Working paperPreprint


Space-time error estimates for deep neural network approximations for differential equations. / Grohs, Philipp; Hornung, Fabian ; Jentzen, Arnulf et al.

In: Advances in Computational Mathematics, Vol. 49, 4, 2023.

Publications: Contribution to journalArticlePeer Reviewed


Variational Monte Carlo on a Budget - Fine-tuning pretrained Neural Wavefunctions. / Scherbela, Michael; Gerard, Leon; Grohs, Philipp.

Advances in Neural Information Processing Systems 36 (NeurIPS 2023). 2023.

Publications: Contribution to bookContribution to proceedingsPeer Reviewed


Exploring Language-independent Digital Speech Biomarkers of Hypokinetic Dysarthria. / Kovac, Daniel; Mekyska, Jiri; Aharonson, Vered et al.

medRxiv, 2022.

Publications: Working paperPreprint


Integral representations of shallow neural network with Rectified Power Unit activation function. / Abdeljawad, Ahmed (Corresponding author); Grohs, Philipp.

In: Neural Networks, Vol. 155, 11.2022, p. 536 - 550.

Publications: Contribution to journalArticlePeer Reviewed


Showing entries 1 - 20 out of 134