45:11A geometric perspective on adversarial machine learning - Rachel Morris (Concordia University)
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A 45-minute video from IVADO: “A geometric perspective on adversarial machine learning - Rachel Morris (Concordia University)”.
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45:11
1:10:41Alignment in Large Language Models: Statistical and Game-Theoretic Perspectives - Weijie Su (UPenn)
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A 71-minute video from IVADO: “Alignment in Large Language Models: Statistical and Game-Theoretic Perspectives - Weijie Su (UPenn)”.
46:36BabyTransformer CODL learns latent domains - Xin Bing (University of Toronto)
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A 47-minute video from IVADO: “BabyTransformer CODL learns latent domains - Xin Bing (University of Toronto)”.
50:27Beyond Calibration: Quantifying Uncertainty via Downstream Decision Making - Geoff Pleiss (UBC)
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A 50-minute video from IVADO: “Beyond Calibration: Quantifying Uncertainty via Downstream Decision Making - Geoff Pleiss (UBC)”.
44:13Case Studies in AI Uncertainty Quantification and Control - Edgar Dobriban (U.Penn)
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A 44-minute video from IVADO: “Case Studies in AI Uncertainty Quantification and Control - Edgar Dobriban (U.Penn)”.
1:03:13Cautious extrapolation of causal predictions from past experimentation - R. Silva (College London)
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A 63-minute video from IVADO: “Cautious extrapolation of causal predictions from past experimentation - R. Silva (College London)”.
49:58Confidence Sets for Causal Orderings - Mladen Kolar (USC)
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A 50-minute video from IVADO: “Confidence Sets for Causal Orderings - Mladen Kolar (USC)”.
55:25Distribution-Informed Learning via Kernelized Stein Discrepancy Calibration - T. Zheng (Columbia U.)
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A 55-minute video from IVADO: “Distribution-Informed Learning via Kernelized Stein Discrepancy Calibration - T. Zheng (Columbia U.)”.
44:13Double Machine Learning for the Treatment of Nonresponse in Survey Sampling - M. Dagdoug (McGill U.)
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A 44-minute video from IVADO: “Double Machine Learning for the Treatment of Nonresponse in Survey Sampling - M. Dagdoug (McGill U.)”.
1:11:55Experimental Progress in Scaling Surface Code and Autonomous Cali | Alexis Morvan, Google Quantum AI
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A 72-minute video from IVADO: “Experimental Progress in Scaling Surface Code and Autonomous Cali | Alexis Morvan, Google Quantum AI”.
50:32Generalization Beyond Observations: A Distributional Perspective - Xinwei Shen (UW Seattle)
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A 51-minute video from IVADO: “Generalization Beyond Observations: A Distributional Perspective - Xinwei Shen (UW Seattle)”.
54:03Global Convergence of Adjoint-Optimized Neural PDEs - Konstantinos Spiliopoulos (Boston University)
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A 54-minute video from IVADO: “Global Convergence of Adjoint-Optimized Neural PDEs - Konstantinos Spiliopoulos (Boston University)”.
47:30Integrating Large-Scale AI Models with Statistical Genetics and Genomics - H. Zhao (Yale)
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A 48-minute video from IVADO: “Integrating Large-Scale AI Models with Statistical Genetics and Genomics - H. Zhao (Yale)”.
41:53PerturbPlan: An analytical framework for designing Perturb-seq experiments - Eugene Katsevich -UPenn
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A 42-minute video from IVADO: “PerturbPlan: An analytical framework for designing Perturb-seq experiments - Eugene Katsevich -UPenn”.
41:53PerturbPlan: An analytical framework for designing Perturbseq experiments - Eugene Katsevich (UPenn)
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A 42-minute video from IVADO: “PerturbPlan: An analytical framework for designing Perturbseq experiments - Eugene Katsevich (UPenn)”.
1:01:42Prediction-Powered Conditional Inference - Xiaowu Dai (UCLA)
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A 62-minute video from IVADO: “Prediction-Powered Conditional Inference - Xiaowu Dai (UCLA)”.
51:11Quantifying and limiting false positives in AI-driven therapeutic discover - Jin Ying (UPenn)
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A 51-minute video from IVADO: “Quantifying and limiting false positives in AI-driven therapeutic discover - Jin Ying (UPenn)”.
1:11:32Quantum neuromorphic computing with superconducting circuits | Danijela Markovic (CNRS / Thales)
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A 72-minute video from IVADO: “Quantum neuromorphic computing with superconducting circuits | Danijela Markovic (CNRS / Thales)”.
1:07:21Representation-Based Diffusion Models - Jian Huang
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A 67-minute video from IVADO: “Representation-Based Diffusion Models - Jian Huang”.
1:03:48Robust Bayesian Learning - Elvezio Ronchetti (University of Geneva)
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A 64-minute video from IVADO: “Robust Bayesian Learning - Elvezio Ronchetti (University of Geneva)”.
43:17Statistical and causal perspectives on machine learning - Erica Moodie (McGill University)
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A 43-minute video from IVADO: “Statistical and causal perspectives on machine learning - Erica Moodie (McGill University)”.
52:22Toward Bayes-Optimal Multimodal In-Context Learning via Cross-Attention Architectures - P. Sur
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A 52-minute video from IVADO: “Toward Bayes-Optimal Multimodal In-Context Learning via Cross-Attention Architectures - P. Sur”.
48:39Towards trustworthy deep learning for inverse problems - B. Adcock (SFU)
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A 49-minute video from IVADO: “Towards trustworthy deep learning for inverse problems - B. Adcock (SFU)”.
1:08:29Understanding Partial Transfer in CNNs viaKronecker Product Regression - Junhui Wang (C.U. HongKong)
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A 68-minute video from IVADO: “Understanding Partial Transfer in CNNs viaKronecker Product Regression - Junhui Wang (C.U. HongKong)”.
1:01:46William Fefferman, University of Chicago — Have We Seen a Demonstration of Experimental Quantum Adva
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A 62-minute video from IVADO: “William Fefferman, University of Chicago — Have We Seen a Demonstration of Experimental Quantum Adva”.