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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 |
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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 |
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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 |
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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 |
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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 |
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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 |
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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 |
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