|
105 | 105 | pdf: ''
|
106 | 106 | repo: published-202412-ambroise-spectral
|
107 | 107 | title: Spectral Bridges
|
108 |
| - url: https://computo.sfds.asso.fr/published-202412-ambroise-spectral/ |
| 108 | + url: '' |
109 | 109 | year: 2024
|
110 | 110 | - abstract': >-
|
111 | 111 | Conformal Inference (CI) is a popular approach for
|
|
261 | 261 | doi: 10.57750/jjza-6j82
|
262 | 262 | draft: false
|
263 | 263 | journal: Computo
|
264 |
| - pdf: https://computo.sfds.asso.fr/published-202402-elmasri-optimal/published-202312-elmasri-optimal.pdf |
| 264 | + pdf: '' |
265 | 265 | repo: published-202402-elmasri-optimal
|
266 | 266 | title: Optimal projection for parametric importance sampling in high dimensions
|
267 |
| - url: https://computo.sfds.asso.fr/published-202402-elmasri-optimal/ |
| 267 | + url: '' |
268 | 268 | year: 2024
|
269 | 269 | - abstract': >-
|
270 | 270 | In numerous applications, cloud of points do seem to
|
|
283 | 283 | pdf: ''
|
284 | 284 | repo: published-202401-adrat-repulsion
|
285 | 285 | title: Point Process Discrimination According to Repulsion
|
286 |
| - url: https://computo.sfds.asso.fr/published_202401_adrat_repulsion/ |
| 286 | + url: '' |
287 | 287 | year: 2024
|
288 | 288 | - abstract': >-
|
289 | 289 | In plant epidemiology, pest abundance is measured in field
|
|
401 | 401 | doi: 10.57750/r5gx-jk62
|
402 | 402 | draft: false
|
403 | 403 | journal: Computo
|
404 |
| - pdf: https://computo.sfds.asso.fr/published-202311-delattre-fim/published-202311-delattre-fim.pdf |
| 404 | + pdf: '' |
405 | 405 | repo: published-202311-delattre-fim
|
406 | 406 | title: Computing an empirical Fisher information matrix estimate in latent variable models through stochastic approximation
|
407 |
| - url: https://computo.sfds.asso.fr/published-202311-delattre-fim/ |
| 407 | + url: '' |
408 | 408 | year: 2023
|
409 | 409 | - abstract': >-
|
410 | 410 | Gaussian Graphical Models (GGMs) are widely used in
|
|
435 | 435 | doi: 10.57750/1f4p-7955
|
436 | 436 | draft: false
|
437 | 437 | journal: Computo
|
438 |
| - pdf: https://computo.sfds.asso.fr/published-202306-sanou-multiscale_glasso/published-202306-sanou-multiscale_glasso.pdf |
| 438 | + pdf: '' |
439 | 439 | repo: published-202306-sanou-multiscale_glasso
|
440 | 440 | title: Inference of Multiscale Gaussian Graphical Models
|
441 |
| - url: https://computo.sfds.asso.fr/published-202306-sanou-multiscale_glasso/ |
| 441 | + url: '' |
442 | 442 | year: 2023
|
443 | 443 | - abstract': >-
|
444 | 444 | Litter is a known cause of degradation in marine
|
|
466 | 466 | doi: 10.57750/845m-f805
|
467 | 467 | draft: false
|
468 | 468 | journal: Computo
|
469 |
| - pdf: https://computo.sfds.asso.fr/published-202301-chagneux-macrolitter/published-202301-chagneux-macrolitter.pdf |
| 469 | + pdf: '' |
470 | 470 | repo: published-202301-chagneux-macrolitter
|
471 | 471 | title: 'Macrolitter video counting on riverbanks using state space models and moving cameras '
|
472 |
| - url: https://computo.sfds.asso.fr/published-202301-chagneux-macrolitter/ |
| 472 | + url: '' |
473 | 473 | year: 2023
|
474 | 474 | - abstract': >-
|
475 | 475 | The package \$\textbackslash textsf\{clayton\}\$ is
|
|
491 | 491 | doi: 10.57750/4szh-t752
|
492 | 492 | draft: false
|
493 | 493 | journal: Computo
|
494 |
| - pdf: https://computo.sfds.asso.fr/published-202301-boulin-clayton/published-202301-boulin-clayton.pdf |
| 494 | + pdf: '' |
495 | 495 | repo: published-202301-boulin-clayton
|
496 | 496 | title: 'A Python Package for Sampling from Copulae: clayton'
|
497 |
| - url: https://computo.sfds.asso.fr/published-202301-boulin-clayton/ |
| 497 | + url: '' |
498 | 498 | year: 2023
|
499 | 499 | - abstract': >-
|
500 | 500 | Deep learning is used in computer vision problems with
|
|
0 commit comments