retrieve:
Return the details about the given Event id.

list:
List all Event objects.

GET /api/v1/events/?format=api&offset=120&ordering=event__canceled
HTTP 200 OK
Allow: GET, HEAD, OPTIONS
Content-Type: application/json
Vary: Accept

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            "title": "Reasoning Under Uncertainty: Trustworthy LLMs for High-Stakes Medicine",
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            "start_date": "2026-06-26",
            "end_date": "2026-06-26",
            "start_time": "09:30:00",
            "end_time": "11:30:00",
            "description": "<u>EDIC candidacy exam</u><br>\r\nExam president: Prof. Robert West<br>\r\nThesis advisor: Prof. Mary-Anne Hartley<br>\r\nCo-examiner: Prof. Martin Jaggi<br>\r\n<br>\r\n<u>Abstract</u><br>\r\nCurrent machine learning systems are very good at tasks reducible to statistical pattern recognition but falter on problems requiring deliberate, structured inference. Clinical reasoning exemplifies the latter: physicians generate hypotheses abductively, revise beliefs probabilistically as evidence accumulates, and choose among actions whose costs are deeply asymmetric. The harm of a missed diagnosis is not the harm of an unnecessary test. Large language models, increasingly deployed for clinical decision support, inherit this limitation. They conflate knowledge with inference: the same parameters that store medical facts are asked to reason over them, which leaves no explicit mechanism to quantify uncertainty, to abstain when evidence is insufficient, or to weight outcomes by their true clinical costs. This work argues that progress toward trustworthy medical AI requires separating the representation of knowledge from the machinery of inference, and grounding the latter in formal frameworks drawn from statistical decision theory. We investigate how these frameworks can be embedded into LLM reasoning pipelines and imposed as external scaffolding around them, maintaining competing hypotheses, guiding evidence gathering, and selecting actions that reflect the asymmetric cost structure of clinical practice. The goal is a class of systems capable of reasoning over their uncertainty, systems that know when they do not know.<br>\r\n<br>\r\n<u>Selected papers</u><br>\r\ncoming soon",
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            "creation_date": "2026-04-29T09:21:38",
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            "id": 71750,
            "title": "Efficiency Datalog Engine for Formal Research",
            "slug": "efficiency-datalog-engine-for-formal-research",
            "event_url": "https://memento.epfl.ch/event/efficiency-datalog-engine-for-formal-research",
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            "start_date": "2026-06-17",
            "end_date": "2026-06-17",
            "start_time": "10:00:00",
            "end_time": "12:00:00",
            "description": "<u>EDIC candidacy exam</u><br>\r\nExam president: Prof. Martin Odersky<br>\r\nThesis advisor: Prof. Christoph Koch<br>\r\nCo-examiner: Prof. Viktor Kuncak<br>\r\n<br>\r\n<u>Abstract</u><br>\r\nDatalog engines are starting to show their potential in a wide range of data-intensive applications. This thesis will investigate techniques for developing a fast Datalog engines, specifically focusing on datalog program rewriting and cost-based optimization for recursive queries. Furthermore, I will explore how Datalog can be specialized for specific tasks, such as static program analysis.<br>\r\n<br>\r\n<u>Selected papers</u><br>\r\ncoming soon",
            "image_description": "",
            "creation_date": "2026-04-29T09:25:41",
            "last_modification_date": "2026-04-29T09:25:41",
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            "spoken_languages": [],
            "speaker": "Christian Fattebert",
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            "id": 71751,
            "title": "From Exploitation to Mitigation: Analyzing Memory Corruption Primitives to Harden the Linux Kernel",
            "slug": "from-exploitation-to-mitigation-analyzing-memory-c",
            "event_url": "https://memento.epfl.ch/event/from-exploitation-to-mitigation-analyzing-memory-c",
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            "lang": "en",
            "start_date": "2026-06-23",
            "end_date": "2026-06-23",
            "start_time": "10:00:00",
            "end_time": "12:00:00",
            "description": "<u>EDIC candidacy exam</u><br>\r\nExam president: Prof. George Candea<br>\r\nThesis advisor: Prof. Mathias Payer<br>\r\nThesis co-advisor: Dr. Anil Kurmus<br>\r\nCo-examiner: Prof. Sanidhya Kashyap<br>\r\n<br>\r\n<u>Abstract</u><br>\r\ncoming soon<br>\r\n<br>\r\n<u>Selected papers</u><br>\r\ncoming soon",
            "image_description": "",
            "creation_date": "2026-04-29T09:44:15",
            "last_modification_date": "2026-04-29T09:44:15",
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            "speaker": "Claudio Migliorelli",
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            "id": 71752,
            "title": "Idiap Create Challenge (ICC), 15th edition",
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            "event_url": "https://memento.epfl.ch/event/idiap-create-challenge-icc-15th-edition",
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            "lang": "en",
            "start_date": "2026-08-20",
            "end_date": "2026-08-28",
            "start_time": null,
            "end_time": null,
            "description": "<div class=\"AutoHeight\">\r\n<div>\r\n<div class=\"post-message post-message--collapsed\">\r\n<div class=\"post-message__text-container\">\r\n<div class=\"post-message__text\">A <strong>9-day AI hackathon</strong> blending learning, innovation, coding, and entrepreneurship. During the 9 days, selected teams will work on-site on their prototypes and get access to dedicated mentorship from Idiap's R&amp;D and AI experts, networking opportunities, speaker sessions and more.<br>\r\n<br>\r\n<strong>This year</strong>, the challenge focuses on the <strong>creative and cultural industries</strong>. Participants are invited to submit projects that <strong>explore new uses, services, or experiences</strong> across nine areas: performing arts and live entertainment, radio and music, fashion, books and publishing, television and film, news and media, architecture and urban planning, the art market, and cultural heritage.<br>\r\nThe event will take place at <strong><a class=\"theme markdown__link\" href=\"https://www.idiap.ch/\" rel=\"noreferrer\" target=\"_blank\">Idiap</a></strong> in <strong>Martigny</strong>, from August 20 until August 28, 2026. Registrations are open until May 31, 2026.<br>\r\n<strong>Full details and registration:</strong> <a class=\"theme markdown__link\" href=\"https://icc.idiap.ch\" rel=\"noreferrer\" target=\"_blank\" title=\"https://icc.idiap.ch\">https://icc.idiap.ch</a></div>\r\n</div>\r\n</div>\r\n</div>\r\n</div>",
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            "creation_date": "2026-04-29T09:47:38",
            "last_modification_date": "2026-05-11T15:38:32",
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            "id": 71753,
            "title": "Metric Sparsification of Inhomogeneous Random Graphs",
            "slug": "metric-sparsification-of-inhomogeneous-random-grap",
            "event_url": "https://memento.epfl.ch/event/metric-sparsification-of-inhomogeneous-random-grap",
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            "start_date": "2026-06-24",
            "end_date": "2026-06-24",
            "start_time": "14:00:00",
            "end_time": "16:00:00",
            "description": "<u>EDIC candidacy exam</u><br>\r\nExam president: Prof. Michael Gastpar<br>\r\nThesis advisor: Prof. Patrick Thiran<br>\r\nCo-examiner: Prof. Olivier Lévêque<br>\r\n<br>\r\n<u>Abstract</u><br>\r\ncoming soon<br>\r\n<br>\r\n<u>Selected papers</u><br>\r\n<a href=\"https://proceedings.neurips.cc/paper_files/paper/2024/hash/41ed4bd197d0a5fa036d361c1fc606ad-Abstract-Conference.html\">Why the Metric Backbone Preserves Community Structure </a><br>\r\n<a href=\"https://www.cambridge.org/core/services/aop-cambridge-core/content/view/ADC162CE72510EA1272B6F5C51FCFBA4/S0001867800007990a.pdf/first_passage_percolation_on_inhomogeneous_random_graphs.pdf\">First Passage Percolation on Inhomogeneous Random Graphs </a><br>\r\n<a href=\"https://projecteuclid.org/journalArticle/Download?urlId=10.1214%2F07-PS094\">A Survey of Random Processes with Reinforcement</a><br>\r\n ",
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            "creation_date": "2026-04-29T09:48:23",
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            "id": 71754,
            "title": "Towards Understanding Large Language Models",
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            "start_date": "2026-06-12",
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            "end_time": "17:30:00",
            "description": "<u>EDIC candidacy exam</u><br>\r\nExam president: Prof. Robert West<br>\r\nThesis advisor: Prof. Nicolas Flammarion<br>\r\nCo-examiner: Prof. Martin Jaggi<br>\r\n<br>\r\n<u>Abstract</u><br>\r\ncoming soon<br>\r\n<br>\r\n<u>Selected papers</u><br>\r\ncoming soon",
            "image_description": "",
            "creation_date": "2026-04-29T09:57:35",
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            "cancel_reason": "",
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            "speaker": "Mark Rofin",
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            "keywords": "EDIC candidacy exam",
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            "id": 71755,
            "title": "Controllable Generative Models via Test-Time Adaptation",
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            "event_url": "https://memento.epfl.ch/event/controllable-generative-models-via-test-time-adapt",
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            "start_date": "2026-07-07",
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            "start_time": "09:30:00",
            "end_time": "11:30:00",
            "description": "<u>EDIC candidacy exam</u><br>\r\nExam president: Prof. Martin Rajman<br>\r\nThesis advisor: Prof. Pascal Fua<br>\r\nCo-examiner: Prof. Jean-Philippe Thiran<br>\r\n<br>\r\n<u>Abstract</u><br>\r\ncoming soon<br>\r\n<br>\r\n<u>Selected papers</u><br>\r\ncoming soon",
            "image_description": "",
            "creation_date": "2026-04-29T10:00:51",
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            "speaker": "Hantao Zhang",
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            "id": 71759,
            "title": "Exploring new dimensions of the DNA damage response",
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            "start_date": "2026-05-28",
            "end_date": "2026-05-28",
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