JuliaCon 2020 | Auto-Optimization and Parallelism in DifferentialEquations.jl | Chris Rackauckas
You might not know all of the latest methods in differential equations, all of the best knobs to tweak, how to properly handle sparsity, or how to parallelize your ...
The Julia Programming Language
Verifying recurrent neural networks using invariant inference by Guy Katz
Abstract: Deep neural networks are revolutionizing the way complex systems are developed. However, these automatically-generated networks are opaque to ...
AISEC
Lecture 5: Parameter Inference Part 2
A coding tutorial showing how to use the Bioscrape python package in conjunction with the Emcee package to infer Chemical Reaction Network (CRN) ...
Build-a-Cell
MapReduce Algorithmics
Sergei Vassilvitskii, Google Parallel and Distributed Algorithms for Inference and Optimization http://simons.berkeley.edu/talks/sergei-vassilvitskii-2013-10-21.
Simons Institute
Edward Ionides: Island filters for inference on metapopulation dynamics
Low-dimensional compartment models for biological systems can be fitted to time series data using Monte Carlo particle filter methods. As dimension increases ...
Centre International de Rencontres Mathématiques
Improving Edge Inferencing
Cheng Wang, senior vice president of engineering at Flex Logix, talks with Semiconductor Engineering about how to improve the efficiency and speed of edge ...
Semiconductor Engineering
Stephen Hoover - Scaling Scikit Learn
Description What do you do if you have a lot of models to fit, don't want to spend all day with your laptop as a space heater, and have access to AWS? Take it to ...
PyData
An Algebraic View of the New Randomized Kaczmarz Linear Solver
Sivan Toledo, Tel Aviv University Parallel and Distributed Algorithms for Inference and Optimization http://simons.berkeley.edu/talks/sivan-toledo-2013-10-23.
Simons Institute
NIPS 2011 Big Learning Workshop - Algorithms, Systems, & Tools for Learning at Scale: NeuFlow...
Big Learning Workshop: Algorithms, Systems, and Tools for Learning at Scale at NIPS 2011 Invited Talk: NeuFlow: A Runtime Reconfigurable Dataflow ...
Google TechTalks
Fine-grain Parallelism of MrBayes on Multi- and(...)
Fine-grain Parallelism of MrBayes on Multi- and Many-core Architectures - Fine-grain Parallelism of MrBayes on Multi- and Many-core Architectures Currently, ...
uvigo
Computationally & Statistically Efficient Distributed Inference with Theoretical Guarantees
Dr. Xiaoming Huo is a professor at the Stewart School of Industrial & Systems Engineering at Georgia Tech. In this recording, he presents a web lecture titled, ...
The Foundations of Biomedical Data Science
Big Data and Large Scale Inference -- Amr Ahmed (Part 2)
MLSS Iceland 2014
JuliaCon 2018 | OMEGA: Fast, causal Inference from Simple Parts | Zenna Tavares
Omega is a library for probabilistic and causal inference. It started with the question “How can we say what we want to say in probabilistic languages?”.
The Julia Programming Language
Mod-01 Lec-34 Lock Free Synchronization,Graph Algorithms
Parallel Computing by Dr. Subodh Kumar,Department of Computer Science and Engineering,IIT Delhi.For more details on NPTEL visit http://nptel.iitm.ac.in.
nptelhrd
NIPS 2011 Big Learning - Algorithms, Systems, & Tools Workshop: No-U-Turn Sampler...
Big Learning Workshop: Algorithms, Systems, and Tools for Learning at Scale at NIPS 2011 Invited Talk: The No-U-Turn Sampler: Adaptively Setting Path ...
Google TechTalks
Parallel Programmability for High Performance Computing
"Chapel: Parallel Programmability for HPC (and your Desktop too!)" This talk describes Chapel, an emerging language from Cray, Inc., that strives to address ...
UW Video
HC32-S4: GPUs and Gaming Architectures
Session 4, Hot Chips 32 (2020), Monday, August 17, 2020. NVIDIA's A100 GPU: Performance and Innovation for GPU Computing Jack Choquette and ...
hotchipsvideos
Variational methods and deep learning for high-dimensional dynamical systems
Speaker: Frank Noé Event: Second Symposium on Machine Learning and Dynamical Systems http://www.fields.utoronto.ca/activities/20-21/dynamical Title: ...
Fields Institute
Streamline Deep Learning for Video Analytics with DeepStream SDK 2 0
Learn how AI-based video analytics applications using DeepStream SDK 2.0 for Tesla can transform video into valuable insights for smart cities. Our latest ...
NVIDIA Developer
Allen School Colloquium: Zhihao Jia (Stanford)
Presentation title: Automated Discovery of Machine Learning Optimizations As an increasingly important workload, machine learning (ML) applications require ...
Paul G. Allen School
A Distributed Deep Learning Approach for the Mitosis Detection from Big Medical Images - Fei Hu IBM
The strongest indicator of a cancer patient's prognosis is the number of mitotic bodies that a pathologist manually counts from the high-resolution whole-slide ...
Databricks
Par Lab Boot Camp @ UC Berkeley - Debugging parallel code
Lecture by Jacob Burnim (UC Berkeley) We survey recent results and useful tools for debugging parallel programs.
CITRIS
tinyML Summit 2019 - Eric Flamand : Ultra Low Power Inference at the Very Edge of the Network
"Ultra Low Power Inference at the Very Edge of the Network" Eric Flamand, CTO, Greenwaves Technologies tinyML Summit 2019 session 1 presentation 3.
tinyML
Parallel Coordinate Descent Methods for Big Data Optimization
Peter Richtarik, University of Edinburgh Parallel and Distributed Algorithms for Inference and Optimization ...
Simons Institute
Load Sharing Mathematics in 2 Parallel operating Transformers
For supplying a load in excess of the rating of an existing transformer, two or more transformers may be connected in parallel with the existing transformer.
Smile and Learn
The Poisson Indel Process
Alexandre Bouchard-Côté, U British Columbia October 18, 2011.
phyloseminar.org
Allen School Distinguished Lecture: Jeff Dean (Google AI)
Lecture Title: Deep Learning to Solve Challenging Problems For the past eight years, Google Research teams have conducted research on difficult problems in ...
Paul G. Allen School
JuliaCon 2017 | HiFrames: High Performance Distributed DataFrames in Julia | Ehsan Totoni
Visit http://julialang.org/ to download Julia.
The Julia Programming Language
Three Goals in Parallel Graph Computations: High Performance, High Productivity, and Reduced Comm...
Three Goals in Parallel Graph Computations: High Performance, High Productivity, and Reduced Communication Aydin Buluç, Lawrence Berkeley National ...
Simons Institute
Reinforcement Learning using Generative Models for Continuous State and Action Space Systems
Rahul Jain (USC) https://simons.berkeley.edu/talks/tbd-241 Reinforcement Learning from Batch Data and Simulation.
Simons Institute
Cloud OnAir: AI Inference on GCP: How to get the best out of GCP VMs with Intel Xeon Scalable
Intel's commitment to AI is simple: help our customers bring their AI vision to life. In this training you will see how engineering collaboration between Intel and ...
Google Cloud Platform
Big Data Serving: The Last Frontier. Processing and Inference at Scale in Real Time by Jon Bratseth
DATA MINER
CRISPRLand: Interpretable Large-Scale Inference of DNA... - Amirali Aghazadeh - VarI - ISMB 2020
CRISPRLand: Interpretable Large-Scale Inference of DNA Repair Landscape Based on a Spectral Approach - Amirali Aghazadeh - VarI - ISMB 2020.
ISCB
Approximate Inference in Graphical Models using LP Relaxations
Graphical models such as Markov random fields have been successfully applied to a wide variety of fields, from computer vision and natural language ...
Microsoft Research
Bayesian inference and big data: are we there yet? by Jose Luis Hidalgo
Session presented at Big Data Spain 2017 Conference 17th Nov 2017 Kinépolis Madrid ...
Big Things Conference
Inference in Time Series
Marc Deisenroth
Inference and Learning in Structured-Output Models for Computer Vision
A large number of problems in computer vision involve predictions over exponentially (or infinitely) large structured-output spaces, e.g. the space of ...
Microsoft Research
Operation and Control of AC Microgrid- Il
This lecture mainly focus on different control techniques used in AC microgrid.
IIT Roorkee July 2018
Systems Biology Approach to Personalized Cancer Therapies - Nitin S. Baliga
Seattle Science Foundation is a non-profit organization dedicated to the international collaboration among physicians, scientists, technologists, engineers and ...
Seattle Science Foundation
AI Inference - Where AI Goes Into Production | Dell Webinar
NG Trainings & Webinars
Massive Parallelism with GPUs in Java by Adam Roberts
Graphic processing units (GPUs) are not limited to traditional scene rendering tasks. They can play a huge role in accelerating applications that have a large ...
Devoxx
JuliaCon 2017 | HiFrames: High Performance Distributed Data Frames in Julia | Ehsan Totoni
Visit http://julialang.org/ to download Julia.
The Julia Programming Language
