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#UncertaintyQuantification

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Valeriy M., PhD, MBA, CQF<p>Thank you to everyone already reading, sharing, and applying these ideas. Let’s keep pushing the boundaries of what machine learning can trust.</p><p><a href="https://sigmoid.social/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>MachineLearning</span></a> <a href="https://sigmoid.social/tags/UncertaintyQuantification" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>UncertaintyQuantification</span></a> <a href="https://sigmoid.social/tags/ConformalPrediction" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ConformalPrediction</span></a> <a href="https://sigmoid.social/tags/AI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AI</span></a> <a href="https://sigmoid.social/tags/DataScience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DataScience</span></a> <a href="https://sigmoid.social/tags/ML" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ML</span></a> <a href="https://sigmoid.social/tags/PolitecnicoDiMilano" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>PolitecnicoDiMilano</span></a> <a href="https://sigmoid.social/tags/3xAuthor" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>3xAuthor</span></a></p><p><a href="https://valeman.gumroad.com/l/advancedconformalprediction" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">valeman.gumroad.com/l/advanced</span><span class="invisible">conformalprediction</span></a></p>
Valeriy M., PhD, MBA, CQF<p>If you're into **AI interpretability, uncertainty quantification**, or tackling the **hallucination problem**, this paper—and the role of conformal prediction—is a must-explore! 📖🔍 </p><p><a href="https://sigmoid.social/tags/AI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AI</span></a> <a href="https://sigmoid.social/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>MachineLearning</span></a> <a href="https://sigmoid.social/tags/LanguageModels" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>LanguageModels</span></a> <a href="https://sigmoid.social/tags/NLP" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>NLP</span></a> <a href="https://sigmoid.social/tags/ConformalPrediction" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ConformalPrediction</span></a> <a href="https://sigmoid.social/tags/UncertaintyQuantification" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>UncertaintyQuantification</span></a> <a href="https://sigmoid.social/tags/Research" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Research</span></a></p>
Martin Trapp<p>The list of accepted papers of our <a href="https://ellis.social/tags/ICCV" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ICCV</span></a> workshop on <a href="https://ellis.social/tags/UncertaintyQuantification" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>UncertaintyQuantification</span></a> for <a href="https://ellis.social/tags/ComputerVision" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ComputerVision</span></a> is out!</p><p>Check out: <a href="https://uncv2023.github.io/papers/" rel="nofollow noopener noreferrer" target="_blank"><span class="invisible">https://</span><span class="">uncv2023.github.io/papers/</span><span class="invisible"></span></a></p>
Gianluca Detommaso<p>🚀 <a href="https://sigmoid.social/tags/AWS" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AWS</span></a> Fortuna is skyrocketing! 🚀 Just a few days, and so many GitHub stars and forks! ⭐️</p><p>Fortuna supports <a href="https://sigmoid.social/tags/ConformalPrediction" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ConformalPrediction</span></a>, <a href="https://sigmoid.social/tags/BayesianInference" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>BayesianInference</span></a> and other methods for <a href="https://sigmoid.social/tags/UncertaintyQuantification" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>UncertaintyQuantification</span></a> in <a href="https://sigmoid.social/tags/DeepLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DeepLearning</span></a>. </p><p>Try it out and let us know! <br><a href="https://github.com/awslabs/fortuna" rel="nofollow noopener noreferrer" target="_blank"><span class="invisible">https://</span><span class="">github.com/awslabs/fortuna</span><span class="invisible"></span></a></p><p>In collaboration with <span class="h-card"><a href="https://sigmoid.social/@cedapprox" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@<span>cedapprox</span></a></span>, <span class="h-card"><a href="https://sigmoid.social/@andrewgwils" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@<span>andrewgwils</span></a></span> and team. </p><p><a href="https://sigmoid.social/tags/uncertainty" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>uncertainty</span></a> <a href="https://sigmoid.social/tags/neuralnetworks" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>neuralnetworks</span></a> <a href="https://sigmoid.social/tags/bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>bayesian</span></a> <a href="https://sigmoid.social/tags/conformal" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>conformal</span></a> <a href="https://sigmoid.social/tags/calibration" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>calibration</span></a> <a href="https://sigmoid.social/tags/jax" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>jax</span></a> <a href="https://sigmoid.social/tags/flax" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>flax</span></a> <a href="https://sigmoid.social/tags/python" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>python</span></a> <a href="https://sigmoid.social/tags/opensource" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>opensource</span></a> <a href="https://sigmoid.social/tags/library" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>library</span></a> <a href="https://sigmoid.social/tags/machinelearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>machinelearning</span></a> <a href="https://sigmoid.social/tags/ai" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ai</span></a></p>
Cedric Archambeau<p>Today, we open sourced Fortuna (<a href="https://github.com/awslabs/fortuna" rel="nofollow noopener noreferrer" target="_blank"><span class="invisible">https://</span><span class="">github.com/awslabs/fortuna</span><span class="invisible"></span></a>) a library for uncertainty quantification.<br>Deep neural networks are often overconfident and do not know what they don’t know. Quantifying the uncertainty in the predictions they make will help deploy deep learning more responsibly and more safely.<br><a href="https://sigmoid.social/tags/responsibleAI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>responsibleAI</span></a> <a href="https://sigmoid.social/tags/ConformalPrediction" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ConformalPrediction</span></a> <a href="https://sigmoid.social/tags/BayesianInference" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>BayesianInference</span></a> <a href="https://sigmoid.social/tags/UncertaintyQuantification" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>UncertaintyQuantification</span></a> <a href="https://sigmoid.social/tags/deeplearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>deeplearning</span></a> <a href="https://sigmoid.social/tags/opensource" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>opensource</span></a></p>
Dominic Boutet<p><a href="https://mastodon.online/tags/arxivfeed" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>arxivfeed</span></a> :</p><p>"Robust DNN Surrogate Models with Uncertainty Quantification via Adversarial Training"<br><a href="https://arxiv.org/abs/2211.09954" rel="nofollow noopener noreferrer" target="_blank"><span class="invisible">https://</span><span class="">arxiv.org/abs/2211.09954</span><span class="invisible"></span></a></p><p><a href="https://mastodon.online/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>MachineLearning</span></a> <a href="https://mastodon.online/tags/DeepLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DeepLearning</span></a> <a href="https://mastodon.online/tags/SurrogateModels" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>SurrogateModels</span></a> <a href="https://mastodon.online/tags/AdversarialTraining" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AdversarialTraining</span></a> <a href="https://mastodon.online/tags/UncertaintyQuantification" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>UncertaintyQuantification</span></a> <a href="https://mastodon.online/tags/Simulation" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Simulation</span></a></p>
Taylor W. Killian<p>Time for an <a href="https://sigmoid.social/tags/introduction" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>introduction</span></a>?</p><p>I'm in the latter stages of my PhD at the University of Toronto (while sitting at MIT). My research focuses on the use of offline <a href="https://sigmoid.social/tags/ReinforcementLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ReinforcementLearning</span></a> and <a href="https://sigmoid.social/tags/UncertaintyQuantification" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>UncertaintyQuantification</span></a> to assess risk and recommend decisions to avoid in safety-critical settings as well as the generalization of policies. I have a particular interest in <a href="https://sigmoid.social/tags/Healthcare" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Healthcare</span></a> challenges but am generally interested in all of RL. </p><p>Soon to be on the job market for Research Scientist positions!</p>
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