Pseudo-Differential Operators: Partial Differential Equations and Time-Frequency Analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
On Hormander operators and non-holonomic geometry by P. Greiner Weyl transforms and the inverse of the sub-Laplacian on the Heisenberg group by A. Dasgupta and M. W. Wong Pseudo-differential calculus on manifolds with geometric singularities by B.-W. Schulze Corner operators and applications to elliptic complexes by C.-I. Martin Ellipticity of a class of corner operators by N. Dines Pseudodifferential methods for boundary value problems by C. L. Epstein Invertibility of parabolic Pseudodifferential operators by V. Rabinovich Semilinear pseudo-differential equations and travelling waves by M. Cappiello, T. Gramchev, and L. Rodino Continuity and compactness properties of pseudo-differential operators by E. Buzano and J. Toft Trace ideals for Fourier integral operators with non-smooth symbols by F. Concetti and J. Toft Schatten-von Neumann norm inequalities for two-wavelet localization operators by V. Catana Why use the S-transform? by R. G. Stockwell Applying the S-transform to magnetic resonance imaging texture analysis by T. A. Bjarnason, S. Drabycz, D. H. Adler, J. G. Cairncross, and J. R. Mitchell Inversion formulas for two-dimensional Stockwell transforms by Y. Liu and M. W. Wong Localization of signal and image features with the TT-transform by C. R. Pinnegar Weight functions in time-frequency analysis by K. Grochenig Shannon type sampling theorems on the Heisenberg group by R. R. Radha and S. Sivananthan Rihaczek transforms and pseudo-differential operators by A. Mohammed and M. W. Wong A unified point of view on time-frequency representations and pseudo-differential operators by P. Boggiatto, G. De Donno, and A. Oliaro Blind source separation using time-frequency analysis by R. Ashino, T. Mandai, A. Morimoto, and F. Sasaki.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it