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2019 Rice Data Science Conference
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Data Science Approaches for Energy
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#1
Welcome
#2
The Rice Data to Knowledge (D2K) Lab
#3
Conference Registration and Networking
#4
Towards Machine Learning Health Systems - Big Data Is Not Enough
#5
Artificial Intelligence in Medicine with Examples in Digital Pathology and Computed Tomography Perfusion
#6
Sharing Resources in the Age of Deep Learning
#7
A Real-Time Streaming Analytic Pipeline for the Auto-Classification of High-Dimensional Celestial Data Using Innovative Hybrid Machine Learning Techniques
#8
Imitate Like a Baby: The Key to Efficient Exploration in Deep Reinforcement Learning
#9
Break
#10
Graph Convolutional Networks: Bringing the Deep Learning Revolution to Graphs
#11
RL in Vehicle Routing and Scheduling
#12
Networking Gala
#13
Data-Driven Super-Parametrization Using Deep Learning: Climate Models that Do Not Affect Our Climate
#14
Prediction Models for Integer and Count Data
#15
Middle-Distant Reading: Big Data Meets Big Humanities Scholarship
#16
HodgeNet: Flow Interpolation with Graph Neural Networks
#17
Dynamic Pricing with Hybrid Linear Contextual Bandit
#18
Identification of Kernels in a Convolutional Neural Network: Connections Between Level Set Equation and Deep Learning for Image Segmentation
#19
E^2-Train: Energy-Efficient Deep Network Training with Data-, Model-, and Algorithm-Level Savings
#20
A Sequential Decision-Making Model for Diagnosis and Medication
#21
Using Deep Learning to Understand Documents
#22
Biomedical Informatics in a Data-driven World
#23
Welcome
#24
Data in the Cloud
#25
Break
#26
Brain Tissue Analytics for Accelerating Drug Discovery
#27
Real-Time Metabolic and Molecular Imaging of Cancer Systems
#28
Lunch
#29
Building Data Science Fluency
#30
Huge Cohorts, Genomics, and Clinical Data to Personalize Medicine
#31
Breakfast
#32
Application of Deep Learning to Automated Diagnosis of Lymphoma with Digital Pathology Images
#33
Composed Relation-Based Learning (CoRL): Predictive Modeling of Drug Side-Effect Relationships
#34
Machine Learning and the Internet of Things Enable Steam Flood Optimization for Improved Oil Production
#35
Measuring Neurodegeneration with Brain Imaging and Digital Device Interaction
#36
Near Real-Time Hydraulic Fracture Event Recognition using Deep Learning Methodology
#37
Object Detection with Deep Learning in the Oil and Gas Industry
#38
Poster Session and Networking
#39
Applying Graph Convolutional Neural Networks for Drug Metabolism Prediction
#40
Automated Field Development Recommendation with Integration of Physics and AI
#41
Porosity Prediction Using the Spectral Decomposition Attributes and Deep Learning
#42
Tensor Networks for Probabilistic Reasoning
#43
Forecast the Future of US Oil and Gas Supply
#44
Automated Formation Top Labeling and Well Depth Matching by Machine Learning
#45
Automated Salt Top Interpretation
#46
A Combinatorial Approach for Single-cell Variant Detection via Phylogenetic Inference
#47
Can Deep Learning Predict Chaos ?
#48
Challenges for the Application of Machine Learning in Real-Time Flood Alert Systems
#49
Computational Techniques for Sensitive and Accurate Threat Screening of Oligonucleotides
#50
Data Mining the Angiome: A New Platform for Characterizing Disease Progression and Drug Efficacy
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Monday, Oct 14
Tuesday, Oct 15
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