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DataLearning@ICL @UCJxOIKpB1MOhBpk3h3uWhog@youtube.com

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56:18
Robert Peharz - TU Graz - Probabilistic Circuits: Deep Probabilistic Models with Tractable Inference
52:35
Gege Wen - Stanford University - CO2 Geological Storage Modelling with Machine Learning
53:51
Jakub Tomczak - Is there a place for Representation Learning in Generative AI?
49:03
Lasse Espeholt - Weather Forecasting using Deep Learning - A paradigm shift (MetNet-3)
50:33
Lluis Guasch - Divide (or convolve) and Conquer: Data Comparison with Wiener Filters
57:50
Francisco Sahli - WarpPINN: Cine-MR image registration with physics-informed neural networks
58:39
Ján Drgoňa - Neuromancer: Differentiable Programming Library for Data-driven Modelling and Control
58:42
Marius Wiggert - Tackling Climate Change with Autonomous Seaweed Farms Hitchhiking on Ocean Currents
01:01:08
Data Learning: Machine Learning in Climate Action
58:25
Data Learning: Towards Better Understanding of Contrastive Learning
50:58
Data Learning: Auto Arborist - Towards Mapping Urban Forests Across North America
51:00
Data Learning: The Role of Data and ML in Enabling Flexible Clean Energy Resources
01:01:21
Data Learning: Exploring AI's Role in Fine Art: An Introduction to Explainable Fine Art
40:27
Data Learning: Graph Representation learning for street networks
38:42
Data Learning: State-of-the-art AI driven Solar PV Generation Forecasts
01:07:04
Data Learning: Causal Representation Learning
01:00:16
Data Learning: Equivariant ML from classical physics
58:23
Data Learning: Overview of machine learning approaches at GSK.ai
51:21
Data Learning: Storage Policy in Continual Learning: Different Approaches for Different Scenarios
51:24
DataLearninig: Interpretable and structure-preserving data-driven methods for physical simulations
59:59
DataLearning: Autoregressive long-context music generation with Perceiver AR
57:27
DataLearning: Physics-Informed Deep Learning - Learning from Small Data
56:44
DataLearning: Physics-Informed Neural Networks in Medicine
43:28
DataLearning: Augmenting the prediction of extubation failure using measures of complexity
44:54
DataLearning: Tackling Fairness, Change, and Polysemy in Word Embeddings
43:52
Data Learning: Predicting material properties with the help of machine learning
58:33
Data Learning: Graph Neural Networks for Charged Particle Reconstruction at Large Hadron Collider
55:54
Data Learning - The Importance of Vegetation & Drought for Global Fire Prediction
01:03:51
Data Learning - Physical inductive biases for learning simulation and scientific discovery
42:48
Data Learning - Adversarial Perturbations in the wild and their applications
50:47
Data Learning - Martian Atmosphere Reconstruction through a Long Short-Term Memory Network
50:36
Data Learning - Generative model-based super-resolution and quality control for cardiac segmentation
01:01:39
Data Learning: Coupling of DNN and physical invariants for turbulent flow surrogate modelling
56:26
Data Learning - The importance of discretization drift in deep learning
01:02:27
Bridging the gap between simulations & real data: domain adaptation for DL in physics & astronomy
58:37
Data Learning - Useful Inductive Biases for Deep Learning in Molecular Science
59:36
Data Learning - The frontier of Simulation-Based Inference
01:03:32
Data Learning - The Future of Finance & Economics: The crossroad between Models, Data, & AI
55:52
Data Learning - Twitter as an alternative data source for international migration studies
01:07:13
Data Learning - Machine Learning for Scientific Discovery, with Examples in Fluid Mechanics
01:05:17
Data Learning - OceanIA: AI and machine learning for understanding the ocean and climate change
01:00:37
Data Learning - Assisting Sampling with Learning: Adaptive Monte Carlo with Normalizing Flows
59:03
Data Learning - Statistical physics of stochastic gradient descent
01:01:04
Data & learning-based approaches for modelling, forecasting & reconstruction of geophysical dynamics
56:14
Data Learning: Exactly solvable models for high-dimensional machine learning problems
57:41
Data Learning: Fully Convolutional Mesh Autoencoder using Efficient Spatially Varying Kernels
21:10
MLDADS 2021 - NVIDIA SimNet™: An AI-Accelerated Multi-Physics Simulation Framework
21:09
MLDADS 2021 - NNs for Conditioning Surface-Based Geological Models with Uncertainty Analysis
17:02
MLDADS 2021 - Data driven deep learning emulators for geophysical forecasting
13:51
MLDADS 2021 - Low dimensional Decompositions for Nonlinear Finite Impulse Response Modelling
01:45
MLDADS 2021 - Introduction
23:42
MLDADS 2021 - Macro to micro & back: Microstates initialization from chaotic aggregate time series
19:33
MLDADS 2021 - Machine learning to correct model error in data assimilation & forecast applications
20:28
MLDADS 2021 - Latent GAN: Using a latent space based GAN for rapid forecasting of CFD models
19:21
MLDADS 2021 - Real time probabilistic inversion of DNN based DeepEM model accounting for model error
17:52
MLDADS 2021 - Deep Learning for Solar Irradiance Nowcasting
20:57
MLDADS 2021 - Auto Encoded Reservoir Computing for Turbulence Learning
16:44
MLDADS 2021 - Automatic differentiated Physics Informed Echo State Network (API ESN)
21:08
MLDADS 2021 - A machine learning method for parameter estimation and sensitivity analysis
14:43
MLDADS 2021 - Data Assimilation using Heteroscedastic Bayesian NN Ensembles for RO Flame Models