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is-small is-link">Go</button> </div> </div> </form> </div> </div> <ol class="breathe-horizontal" start="1"> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.00621">arXiv:2411.00621</a> <span> [<a href="https://arxiv.org/pdf/2411.00621">pdf</a>, <a href="https://arxiv.org/format/2411.00621">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Machine Learning">stat.ML</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Methodology">stat.ME</span> </div> </div> <p class="title is-5 mathjax"> Nonparametric estimation of Hawkes processes with RKHSs </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Bonnet%2C+A">Anna Bonnet</a>, <a href="/search/cs?searchtype=author&query=Sangnier%2C+M">Maxime Sangnier</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.00621v1-abstract-short" style="display: inline;"> This paper addresses nonparametric estimation of nonlinear multivariate Hawkes processes, where the interaction functions are assumed to lie in a reproducing kernel Hilbert space (RKHS). Motivated by applications in neuroscience, the model allows complex interaction functions, in order to express exciting and inhibiting effects, but also a combination of both (which is particularly interesting to… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.00621v1-abstract-full').style.display = 'inline'; document.getElementById('2411.00621v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.00621v1-abstract-full" style="display: none;"> This paper addresses nonparametric estimation of nonlinear multivariate Hawkes processes, where the interaction functions are assumed to lie in a reproducing kernel Hilbert space (RKHS). Motivated by applications in neuroscience, the model allows complex interaction functions, in order to express exciting and inhibiting effects, but also a combination of both (which is particularly interesting to model the refractory period of neurons), and considers in return that conditional intensities are rectified by the ReLU function. The latter feature incurs several methodological challenges, for which workarounds are proposed in this paper. In particular, it is shown that a representer theorem can be obtained for approximated versions of the log-likelihood and the least-squares criteria. Based on it, we propose an estimation method, that relies on two simple approximations (of the ReLU function and of the integral operator). We provide an approximation bound, justifying the negligible statistical effect of these approximations. Numerical results on synthetic data confirm this fact as well as the good asymptotic behavior of the proposed estimator. It also shows that our method achieves a better performance compared to related nonparametric estimation techniques and suits neuronal applications. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.00621v1-abstract-full').style.display = 'none'; document.getElementById('2411.00621v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 1 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2311.16079">arXiv:2311.16079</a> <span> [<a href="https://arxiv.org/pdf/2311.16079">pdf</a>, <a href="https://arxiv.org/format/2311.16079">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computation and Language">cs.CL</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Artificial Intelligence">cs.AI</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> </div> </div> <p class="title is-5 mathjax"> MEDITRON-70B: Scaling Medical Pretraining for Large Language Models </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Chen%2C+Z">Zeming Chen</a>, <a href="/search/cs?searchtype=author&query=Cano%2C+A+H">Alejandro Hern谩ndez Cano</a>, <a href="/search/cs?searchtype=author&query=Romanou%2C+A">Angelika Romanou</a>, <a href="/search/cs?searchtype=author&query=Bonnet%2C+A">Antoine Bonnet</a>, <a href="/search/cs?searchtype=author&query=Matoba%2C+K">Kyle Matoba</a>, <a href="/search/cs?searchtype=author&query=Salvi%2C+F">Francesco Salvi</a>, <a href="/search/cs?searchtype=author&query=Pagliardini%2C+M">Matteo Pagliardini</a>, <a href="/search/cs?searchtype=author&query=Fan%2C+S">Simin Fan</a>, <a href="/search/cs?searchtype=author&query=K%C3%B6pf%2C+A">Andreas K枚pf</a>, <a href="/search/cs?searchtype=author&query=Mohtashami%2C+A">Amirkeivan Mohtashami</a>, <a href="/search/cs?searchtype=author&query=Sallinen%2C+A">Alexandre Sallinen</a>, <a href="/search/cs?searchtype=author&query=Sakhaeirad%2C+A">Alireza Sakhaeirad</a>, <a href="/search/cs?searchtype=author&query=Swamy%2C+V">Vinitra Swamy</a>, <a href="/search/cs?searchtype=author&query=Krawczuk%2C+I">Igor Krawczuk</a>, <a href="/search/cs?searchtype=author&query=Bayazit%2C+D">Deniz Bayazit</a>, <a href="/search/cs?searchtype=author&query=Marmet%2C+A">Axel Marmet</a>, <a href="/search/cs?searchtype=author&query=Montariol%2C+S">Syrielle Montariol</a>, <a href="/search/cs?searchtype=author&query=Hartley%2C+M">Mary-Anne Hartley</a>, <a href="/search/cs?searchtype=author&query=Jaggi%2C+M">Martin Jaggi</a>, <a href="/search/cs?searchtype=author&query=Bosselut%2C+A">Antoine Bosselut</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2311.16079v1-abstract-short" style="display: inline;"> Large language models (LLMs) can potentially democratize access to medical knowledge. While many efforts have been made to harness and improve LLMs' medical knowledge and reasoning capacities, the resulting models are either closed-source (e.g., PaLM, GPT-4) or limited in scale (<= 13B parameters), which restricts their abilities. In this work, we improve access to large-scale medical LLMs by rele… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2311.16079v1-abstract-full').style.display = 'inline'; document.getElementById('2311.16079v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2311.16079v1-abstract-full" style="display: none;"> Large language models (LLMs) can potentially democratize access to medical knowledge. While many efforts have been made to harness and improve LLMs' medical knowledge and reasoning capacities, the resulting models are either closed-source (e.g., PaLM, GPT-4) or limited in scale (<= 13B parameters), which restricts their abilities. In this work, we improve access to large-scale medical LLMs by releasing MEDITRON: a suite of open-source LLMs with 7B and 70B parameters adapted to the medical domain. MEDITRON builds on Llama-2 (through our adaptation of Nvidia's Megatron-LM distributed trainer), and extends pretraining on a comprehensively curated medical corpus, including selected PubMed articles, abstracts, and internationally-recognized medical guidelines. Evaluations using four major medical benchmarks show significant performance gains over several state-of-the-art baselines before and after task-specific finetuning. Overall, MEDITRON achieves a 6% absolute performance gain over the best public baseline in its parameter class and 3% over the strongest baseline we finetuned from Llama-2. Compared to closed-source LLMs, MEDITRON-70B outperforms GPT-3.5 and Med-PaLM and is within 5% of GPT-4 and 10% of Med-PaLM-2. We release our code for curating the medical pretraining corpus and the MEDITRON model weights to drive open-source development of more capable medical LLMs. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2311.16079v1-abstract-full').style.display = 'none'; document.getElementById('2311.16079v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 27 November, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2023. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1711.09713">arXiv:1711.09713</a> <span> [<a href="https://arxiv.org/pdf/1711.09713">pdf</a>, <a href="https://arxiv.org/format/1711.09713">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Software Engineering">cs.SE</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Distributed, Parallel, and Cluster Computing">cs.DC</span> </div> </div> <p class="title is-5 mathjax"> Boutiques: a flexible framework for automated application integration in computing platforms </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Glatard%2C+T">Tristan Glatard</a>, <a href="/search/cs?searchtype=author&query=Kiar%2C+G">Gregory Kiar</a>, <a href="/search/cs?searchtype=author&query=Aumentado-Armstrong%2C+T">Tristan Aumentado-Armstrong</a>, <a href="/search/cs?searchtype=author&query=Beck%2C+N">Natacha Beck</a>, <a href="/search/cs?searchtype=author&query=Bellec%2C+P">Pierre Bellec</a>, <a href="/search/cs?searchtype=author&query=Bernard%2C+R">R茅mi Bernard</a>, <a href="/search/cs?searchtype=author&query=Bonnet%2C+A">Axel Bonnet</a>, <a href="/search/cs?searchtype=author&query=Camarasu-Pop%2C+S">Sorina Camarasu-Pop</a>, <a href="/search/cs?searchtype=author&query=Cervenansky%2C+F">Fr茅d茅ric Cervenansky</a>, <a href="/search/cs?searchtype=author&query=Das%2C+S">Samir Das</a>, <a href="/search/cs?searchtype=author&query=da+Silva%2C+R+F">Rafael Ferreira da Silva</a>, <a href="/search/cs?searchtype=author&query=Flandin%2C+G">Guillaume Flandin</a>, <a href="/search/cs?searchtype=author&query=Girard%2C+P">Pascal Girard</a>, <a href="/search/cs?searchtype=author&query=Gorgolewski%2C+K+J">Krzysztof J. Gorgolewski</a>, <a href="/search/cs?searchtype=author&query=Guttmann%2C+C+R+G">Charles R. G. Guttmann</a>, <a href="/search/cs?searchtype=author&query=Hayot-Sasson%2C+V">Val茅rie Hayot-Sasson</a>, <a href="/search/cs?searchtype=author&query=Quirion%2C+P">Pierre-Olivier Quirion</a>, <a href="/search/cs?searchtype=author&query=Rioux%2C+P">Pierre Rioux</a>, <a href="/search/cs?searchtype=author&query=Rousseau%2C+M">Marc-Eienne Rousseau</a>, <a href="/search/cs?searchtype=author&query=Evans%2C+A+C">Alan C. Evans</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="1711.09713v1-abstract-short" style="display: inline;"> We present Boutiques, a system to automatically publish, integrate and execute applications across computational platforms. Boutiques applications are installed through software containers described in a rich and flexible JSON language. A set of core tools facilitate the construction, validation, import, execution, and publishing of applications. Boutiques is currently supported by several distinc… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1711.09713v1-abstract-full').style.display = 'inline'; document.getElementById('1711.09713v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1711.09713v1-abstract-full" style="display: none;"> We present Boutiques, a system to automatically publish, integrate and execute applications across computational platforms. Boutiques applications are installed through software containers described in a rich and flexible JSON language. A set of core tools facilitate the construction, validation, import, execution, and publishing of applications. Boutiques is currently supported by several distinct virtual research platforms, and it has been used to describe dozens of applications in the neuroinformatics domain. We expect Boutiques to improve the quality of application integration in computational platforms, to reduce redundancy of effort, to contribute to computational reproducibility, and to foster Open Science. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1711.09713v1-abstract-full').style.display = 'none'; document.getElementById('1711.09713v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 7 November, 2017; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2017. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">10 pages</span> </p> </li> </ol> <div class="is-hidden-tablet">  <span class="help" style="display: inline-block;"><a href="https://github.com/arXiv/arxiv-search/releases">Search 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