Shows

What NLP Tells Us About COVID-19 and Mental Health with Johannes Eichstaedt

Human-AI Collaboration for Creativity with Devi Parikh

Neural Augmentation for Wireless Communication with Max Welling

Quantum Machine Learning: The Next Frontier? with Iordanis Kerenidis

ML and Epidemiology with Elaine Nsoesie

Language (Technology) Is Power: Exploring the Inherent Complexity of NLP Systems with Hal Daumé III

Graph ML Research at Twitter with Michael Bronstein

Panel: The Great ML Language (Un)Debate!

What the Data Tells Us About COVID-19 with Eric Topol

The Case for Hardware-ML Model Co-design with Diana Marculescu

Computer Vision for Remote AR with Flora Tasse

Deep Learning for Automatic Basketball Video Production with Julian Quiroga

How External Auditing is Changing the Facial Recognition Landscape with Deb Raji

AI for High-Stakes Decision Making with Hima Lakkaraju

Invariance, Geometry and Deep Neural Networks with Pavan Turaga

Channel Gating for Cheaper and More Accurate Neural Nets with Babak Ehteshami Bejnordi

Machine Learning Commerce at Square with Marsal Gavalda

Cell Exploration with ML at the Allen Institute w/ Jianxu Chen

Neural Arithmetic Units & Experiences as an Independent ML Researcher with Andreas Madsen

2020: A Critical Inflection Point for Responsible AI with Rumman Chowdhury

Panel: Advancing Your Data Science Career During the Pandemic

Engineering a Less Artificial Intelligence with Andreas Tolias

Rethinking Model Size: Train Large, Then Compress with Joseph Gonzalez

The Physics of Data with Alpha Lee

Is Linguistics Missing from NLP Research? w/ Emily M. Bender

Disrupting DeepFakes: Adversarial Attacks Against Conditional Image Translation Networks with Nataniel Ruiz

Understanding the COVID-19 Data Quality Problem with Sherri Rose

The Whys and Hows of Managing Machine Learning Artifacts with Lukas Biewald

Language Modeling and Protein Generation at Salesforce with Richard Socher

AI Research at JPMorgan Chase with Manuela Veloso

Panel: Responsible Data Science in the Fight Against COVID-19

Adversarial Examples Are Not Bugs, They Are Features with Aleksander Madry

AI for Social Good: Why “Good” isn’t Enough with Ben Green

The Evolution of Evolutionary AI with Risto Miikkulainen

Neural Architecture Search and Google’s New AutoML Zero with Quoc Le

Automating Electronic Circuit Design with Deep RL w/ Karim Beguir

Neural Ordinary Differential Equations with David Duvenaud

The Measure and Mismeasure of Fairness with Sharad Goel

Simulating the Future of Traffic with RL w/ Cathy Wu

Consciousness and COVID-19 with Yoshua Bengio

Geometry-Aware Neural Rendering with Josh Tobin

The Third Wave of Robotic Learning with Ken Goldberg

Learning Visiolinguistic Representations with ViLBERT w/ Stefan Lee

Upside-Down Reinforcement Learning with Jürgen Schmidhuber

SLIDE: Smart Algorithms over Hardware Acceleration for Large-Scale Deep Learning with Beidi Chen

Advances in Reinforcement Learning with Sergey Levine

Secrets of a Kaggle Grandmaster with David Odaibo

NLP for Mapping Physics Research with Matteo Chinazzi

Metric Elicitation and Robust Distributed Learning with Sanmi Koyejo

High-Dimensional Robust Statistics with Ilias Diakonikolas

How AI Predicted the Coronavirus Outbreak with Kamran Khan

Turning Ideas into ML Powered Products with Emmanuel Ameisen

Algorithmic Injustices and Relational Ethics with Abeba Birhane

AI for Agriculture and Global Food Security with Nemo Semret

Practical Differential Privacy at LinkedIn with Ryan Rogers

Networking Optimizations for Multi-Node Deep Learning on Kubernetes with Erez Cohen

Managing Research Needs at the University of Michigan using Kubernetes with Bob Killen

Scalable and Maintainable Workflows at Lyft with Flyte w/ Haytham AbuelFutuh and Ketan Umare

Causality 101 with Robert Osazuwa Ness

PaccMannRL: Designing Anticancer Drugs with Reinforcement Learning w/ Jannis Born

Social Intelligence with Blaise Aguera y Arcas

Music & AI Plus A Geometric Perspective on Reinforcement Learning

Trends in Computer Vision with Amir Zamir

Trends in Natural Language Processing with Nasrin Mostafazadeh

Trends in Fairness and AI Ethics with Timnit Gebru

Trends in Reinforcement Learning with Chelsea Finn

Trends in Machine Learning & Deep Learning with Zack Lipton

FaciesNet & Machine Learning Applications in Energy with Mohamed Sidahmed

Machine Learning: A New Approach to Drug Discovery with Daphne Koller

Sensory Prediction Error Signals in the Neocortex with Blake Richards

How to Know with Celeste Kidd

Using Deep Learning to Predict Wildfires with Feng Yan

Advancing Machine Learning at Capital One with Dave Castillo

Helping Fish Farmers Feed the World with Deep Learning w/ Bryton Shang

Metaflow, a Human-Centric Framework for Data Science with Ville Tuulos

Single Headed Attention RNN: Stop Thinking With Your Head with Stephen Merity

Automated Model Tuning with SigOpt – Democast #2

Automated Machine Learning with Erez Barak

Responsible AI in Practice with Sarah Bird

Enterprise Readiness, MLOps and Lifecycle Management with Jordan Edwards

DevOps for ML with Dotscience – Democast #1

Building an Autonomous Knowledge Graph with Mike Tung

The Next Generation of Self-Driving Engineers with Aaron Ma

Spiking Neural Networks: A Primer with Terrence Sejnowski

Bridging the Patient-Physician Gap with ML and Expert Systems w/ Xavier Amatriain

What Does it Mean for a Machine to “Understand”? with Thomas Dietterich

Scaling TensorFlow at LinkedIn with Jonathan Hung

Machine Learning at GitHub with Omoju Miller

Using AI to Diagnose and Treat Neurological Disorders with Archana Venkataraman

Deep Learning for Earthquake Aftershock Patterns with Phoebe DeVries & Brendan Meade

Live from TWIMLcon! Operationalizing Responsible AI

Live from TWIMLcon! Scaling ML in the Traditional Enterprise

Live from TWIMLcon! Culture & Organization for Effective ML at Scale

Live from TWIMLcon! Use-Case Driven ML Platforms with Franziska Bell

Live from TWIMLcon! Operationalizing ML at Scale with Hussein Mehanna

Live from TWIMLcon! Encoding Company Culture in Applied AI Systems

Live from TWIMLcon! Overcoming the Barriers to Deep Learning in Production with Andrew Ng

The Future of Mixed-Autonomy Traffic with Alexandre Bayen

Deep Reinforcement Learning for Logistics at Instadeep with Karim Beguir

Deep Learning with Structured Data w/ Mark Ryan

Time Series Clustering for Monitoring Fueling Infrastructure Performance with Kalai Ramea

Swarm AI for Event Outcome Prediction with Gregg Willcox

Rebooting AI: What’s Missing, What’s Next with Gary Marcus

DeepQB: Deep Learning to Quantify Quarterback Decision-Making with Brian Burke

Measuring Performance Under Pressure Using ML with Lotte Bransen

Managing Deep Learning Experiments with Lukas Biewald

Re-Architecting Data Science at iRobot with Angela Bassa

Disentangled Representations & Google Research Football with Olivier Bachem

Neural Network Quantization and Compression with Tijmen Blankevoort

Identifying New Materials with NLP with Anubhav Jain

The Problem with Black Boxes with Cynthia Rudin

Human-Robot Interaction and Empathy with Kate Darling

Automated ML for RNA Design with Danny Stoll

Developing a Brain Atlas Using Deep Learning with Theofanis Karayannis

Environmental Impact of Large-Scale NLP Model Training with Emma Strubell

“Fairwashing” and the Folly of ML Solutionism with Zachary Lipton

Retinal Image Generation for Disease Discovery with Stephen Odaibo

Real World Model Explainability with Rayid Ghani

Inspiring New Machine Learning Platforms with Bioelectric Computation with Michael Levin

Simulation and Synthetic Data for Computer Vision with Batu Arisoy

Spiking Neural Nets and ML as a Systems Challenge with Jeff Gehlhaar

Transforming Oil & Gas with AI with Adi Bhashyam and Daniel Jeavons

Fast Radio Burst Pulse Detection with Gerry Zhang

Tracking CO2 Emissions with Machine Learning with Laurence Watson

Topic Modeling for Customer Insight at USAA with William Fehlman

Phronesis of AI in Radiology with Judy Gichoya

The Ethics of AI-Enabled Surveillance with Karen Levy

Supporting Rapid Model Development at Two Sigma with Matt Adereth & Scott Clark

Scaling Model Training with Kubernetes at Stripe with Kelley Rivoire

Productizing ML at Scale at Twitter with Yi Zhuang

Snorkel: A System for Fast Training Data Creation with Alex Ratner

Advancing Autonomous Vehicle Development Using Distributed Deep Learning with Adrien Gaidon

Are We Being Honest About How Difficult AI Really Is? with David Ferrucci

Gauge Equivariant CNNs, Generative Models, and the Future of AI with Max Welling

Can We Trust Scientific Discoveries Made Using Machine Learning? with Genevera Allen

Creative Adversarial Networks for Art Generation with Ahmed Elgammal

Diagnostic Visualization for Machine Learning with YellowBrick w/ Rebecca Bilbro

Librosa: Audio and Music Processing in Python with Brian McFee

Practical Natural Language Processing with spaCy and Prodigy w/ Ines Montani

Scaling Jupyter Notebooks with Luciano Resende

Fighting Fake News and Deep Fakes with Machine Learning w/ Delip Rao

Maintaining Human Control of Artificial Intelligence with Joanna Bryson

Intelligent Infrastructure Management with Pankaj Goyal & Rochna Dhand

Organizing for Successful Data Science at Stitch Fix with Eric Colson

End-to-End Data Science to Drive Business Decisions at LinkedIn with Burcu Baran

Learning with Limited Labeled Data with Shioulin Sam

cuDF, cuML & RAPIDS: GPU Accelerated Data Science with Paul Mahler

Edge AI for Smart Manufacturing with Trista Chen

Machine Learning for Security and Security for Machine Learning with Nicole Nichols

Domain Adaptation and Generative Models for Single Cell Genomics with Gerald Quon

Mapping Dark Matter with Bayesian Neural Networks w/ Yashar Hezaveh

Deep Learning for Population Genetic Inference with Dan Schrider

Empathy in AI with Rob Walker

Benchmarking Custom Computer Vision Services at Urban Outfitters with Tom Szumowski

A Quantum Machine Learning Algorithm Takedown with Ewin Tang

Pragmatic Quantum Machine Learning with Peter Wittek

Supporting TensorFlow at Airbnb with Alfredo Luque

Mining the Vatican Secret Archives with TensorFlow w/ Elena Nieddu

Exploring TensorFlow 2.0 with Paige Bailey

Privacy-Preserving Decentralized Data Science with Andrew Trask

The Unreasonable Effectiveness of the Forget Gate with Jos Van Der Westhuizen

Building a Recommendation Agent for The North Face with Andrew Guldman

Active Learning for Materials Design with Kevin Tran

Deep Learning in Optics with Aydogan Ozcan

Scaling Machine Learning on Graphs at LinkedIn with Hema Raghavan and Scott Meyer

Safer Exploration in Deep Reinforcement Learning using Action Priors with Sicelukwanda Zwane

Human-Centered Design with Mira Lane

Fairness in Machine Learning with Hanna Wallach

AI in Healthcare with Peter Lee

An Optimized Recurrent Unit for Ultra-Low Power Acoustic Event Detection with Justice Amoh

Pathologies of Neural Models and Interpretability with Alvin Grissom II

AI for Earth with Lucas Joppa

AI for Accessibility with Wendy Chisholm

AI for Humanitarian Action with Justin Spelhaug

Teaching AI to Preschoolers with Randi Williams

Holistic Optimization of the LinkedIn Newsfeed with Tim Jurka

AI at the Edge at Qualcomm with Gary Brotman

AI Innovation at CES – Video Exclusive!!

Self-Tuning Services via Real-Time Machine Learning with Vladimir Bychkovsky

Building a Recommender System from Scratch at 20th Century Fox with JJ Espinoza

Legal and Policy Implications of Model Interpretability with Solon Barocas

Trends in Computer Vision with Siddha Ganju

Trends in Reinforcement Learning with Simon Osindero

Trends in Natural Language Processing with Sebastian Ruder

Trends in Machine Learning with Anima Anandkumar

Trends in Deep Learning with Jeremy Howard

Training Large-Scale Deep Nets with RL with Nando de Freitas

Making Algorithms Trustworthy with David Spiegelhalter

Designing Computer Systems for Software with Kunle Olukotun

Operationalizing Ethical AI with Kathryn Hume

Approaches to Fairness in Machine Learning with Richard Zemel

Trust and AI with Parinaz Sobhani

Unbiased Learning from Biased User Feedback with Thorsten Joachims

Language Parsing and Character Mining with Jinho Choi

re:Invent Roundup Roundtable 2018 with Dave McCrory and Val Bercovici

Knowledge Graphs and Expert Augmentation with Marisa Boston

ML/DL for Non-Stationary Time Series Analysis in Financial Markets and Beyond with Stuart Reid

Industrializing Machine Learning at Shell with Daniel Jeavons

Resurrecting a Recommendations Platform at Comcast with Leemay Nassery

Productive Machine Learning at LinkedIn with Bee-Chung Chen

Scaling Deep Learning on Kubernetes at OpenAI with Christopher Berner

Bighead: Airbnb’s Machine Learning Platform with Atul Kale

Facebook’s FBLearner Platform with Aditya Kalro

Geometric Statistics in Machine Learning with geomstats w/ Nina Miolane

Milestones in Neural Natural Language Processing with Sebastian Ruder

Natural Language Processing at StockTwits with Garrett Hoffman

Advanced Reinforcement Learning & Data Science for Social Impact with Vukosi Marivate

AI Ethics, Strategic Decisioning and Game Theory with Osonde Osoba

Acoustic Word Embeddings for Low Resource Speech Processing with Herman Kamper

Learning Representations for Visual Search with Naila Murray

Evaluating Model Explainability Methods with Sara Hooker

Graph Analytic Systems with Zachary Hanif

Diversification in Recommender Systems with Ahsan Ashraf

The Fastai v1 Deep Learning Framework with Jeremy Howard

Federated ML for Edge Applications with Justin Norman

Exploring Dark Energy & Star Formation with ML w/ Viviana Acquaviva

Document Vectors in the Wild with James Dreiss

Applied Machine Learning for Publishers with Naveed Ahmad

Anticipating Superintelligence with Nick Bostrom

Can We Train an AI to Understand Body Language? with Hanbyul Joo

Biological Particle Identification and Tracking with Jay Newby

AI for Content Creation with Debajyoti Ray

Deep Reinforcement Learning Primer and Research Frontiers with Kamyar Azizzadenesheli

OpenAI Five with Christy Dennison

How ML Keeps Shelves Stocked at Home Depot with Pat Woowong

Contextual Modeling for Language and Vision with Nasrin Mostafazadeh

ML for Understanding Satellite Imagery at Scale with Kyle Story

Generating Ground-Level Images From Overhead Imagery Using GANs with Yi Zhu

Vision Systems for Planetary Landers and Drones with Larry Matthies

Learning Semantically Meaningful and Actionable Representations with Ashutosh Saxena

AI Innovation for Clinical Decision Support with Joe Connor

Dynamic Visual Localization and Segmentation with Laura Leal-Taixé

Conversational AI for the Intelligent Workplace with Gillian McCann

Computer Vision and Intelligent Agents for Wildlife Conservation with Jason Holmberg

Pragmatic Deep Learning for Medical Imagery with Prashant Warier

Taskonomy: Disentangling Transfer Learning for Perception (CVPR 2018 Best Paper Winner) with Amir Zamir

Predicting Metabolic Pathway Dynamics with Machine Learning w/ Zak Costello

Machine Learning to Discover Physics and Engineering Principles with Nathan Kutz

Automating Complex Internal Processes with AI w/ Alexander Chukovski

Designing Better Sequence Models with RNNs with Adji Bousso Dieng

Love Love: AI and ML in Tennis with Stephanie Kovalchik

Growth Hacking Sports with Machine Learning w/ Noah Gift

Fine-Grained Player Prediction in Sports with Jennifer Hobbs

Targeted Ticket Sales Using ML for the Portland Trail Blazers w/ Mike Schumacher & Chenhui Hu

AI for Athlete Optimization with Sinead Flahive

Omni-Channel Customer Experiences with Vince Jeffs

Workforce Intelligence for Automation & Productivity with Michael Kempe

Data Platforms for Decision Automation at Scotiabank with Jim Saleh

Towards the Self-Driving Enterprise with Kirk Borne

How a Global Energy Company Adopts ML & AI with Nicholas Osborn

Problem Formulation for Machine Learning with Romer Rosales

AI for Materials Discovery with Greg Mulholland

Data Innovation & AI at Capital One with Adam Wenchel

Deep Gradient Compression for Distributed Training with Song Han

Masked Autoregressive Flow for Density Estimation with George Papamakarios

Training Data for Computer Vision at Figure Eight with Qazaleh Mirsharif

Agile Data Science with Sarah Aerni

Tensor Operations for Machine Learning with Anima Anandkumar

Deep Learning for Live-Cell Imaging with David Van Valen

Checking in with the Master with Garry Kasparov

Exploring AI-Generated Music with Taryn Southern

Practical Deep Learning with Rachel Thomas

Kinds of Intelligence: Types, Tests & Meeting the Needs of Society w/ Jose Hernandez-Orallo

Taming arXiv with Natural Language Processing w/ John Bohannon

Epsilon Software for Private Machine Learning with Chang Liu

Scalable Differential Privacy for Deep Learning with Nicolas Papernot

Differential Privacy at Bluecore with Zahi Karam

Differential Privacy Theory & Practice with Aaron Roth

Optimal Transport and Machine Learning with Marco Cuturi

Collecting and Annotating Data for AI with Kiran Vajapey

Autonomous Aerial Guidance, Navigation and Control Systems with Christopher Lum

Infrastructure for Autonomous Vehicles with Missy Cummings

Hyper-Personalizing the Customer Experience with AI w/ Rob Walker

Information Extraction from Natural Document Formats with David Rosenberg

Human-in-the-Loop AI for Emergency Response and More with Robert Munro

Systems and Software for Machine Learning at Scale with Jeff Dean

Semantic Segmentation of 3D Point Clouds with Lyne Tchapmi

Predicting Cardiovascular Risk Factors from Eye Images with Ryan Poplin

Reproducibility and the Philosophy of Data with Clare Gollnick

Surveying the Connected Car Landscape with GK Senthil

Adversarial Attacks Against Reinforcement Learning Agents with Ian Goodfellow & Sandy Huang

Towards Abstract Robotic Understanding with Raja Chatila

Discovering Exoplanets with Deep Learning with Chris Shallue

Learning Active Learning from Data with Ksenia Konyushkova

Scaling Machine Learning at Uber with Mike Del Balso

Inverse Programming for Deeper AI with Zenna Tavares

Statistical Relational Artificial Intelligence with Sriraam Natarajan

Classical Machine Learning for Infant Medical Diagnosis with Charles Onu

Learning “Common Sense” and Physical Concepts with Roland Memisevic

Trust in Human-Robot/AI Interactions with Ayanna Howard

Data Science for Poaching Prevention and Disease Treatment with Nyalleng Moorosi

Security and Safety in AI: Adversarial Examples, Bias and Trust with Moustapha Cissé

Peering into the Home with Aerial’s Wifi Motion Analytics w/ Michel Allegue & Negar Ghourchian

Physiology-Based Models for Fitness and Training with Firstbeat w/ Ilkka Korhonen

Machine Learning for Signal Processing Applications with Stuart Feffer & Brady Tsai

Personalizing the Ferrari Challenge Experience with Andy Keller and Emile Chin-Dickey

Deep Learning for 3D Sensors and Cameras in Lighthouse with Alex Teichman

Computer Vision for Cozmo, the Cutest Toy Robot Everrrrr! with Andrew Stein

Expectation Maximization, Gaussian Mixtures & Belief Propagation, OH MY! with Inmar Givoni

A Linear-Time Kernel Goodness-of-Fit Test with Wittawat Jitkrittum, Zoltan Szabo, Kenji Fukumizu, Arthur Gretton – NIPS Best Paper ’17

Safe and Nested Subgame Solving for Imperfect-Information Games with Tuomas Sandholm – NIPS Best Paper ’17

Separating Vocals in Recorded Music at Spotify with Eric Humphrey

Accelerating Deep Learning with Mixed Precision Arithmetic with Greg Diamos

Composing Graphical Models With Neural Networks with David Duvenaud

Embedded Deep Learning at Deep Vision with Siddha Ganju

Neuroevolution: Evolving Novel Neural Network Architectures with Kenneth Stanley

A Quantum Computing Primer and Implications for AI with Davide Venturelli

Learning State Representations with Yael Niv

Philosophy of Intelligence with Matthew Crosby

Geometric Deep Learning with Joan Bruna and Michael Bronstein

AI at the NASA Frontier Development Lab with Sara Jennings, Timothy Seabrook and Andres Rodriguez

Using Deep Learning and Google Street View to Estimate Demographics with Timnit Gebru

Integrative Learning for Robotic Systems with Aaron Ames

Visual Recognition in the Cloud for Law Enforcement with Chris Adzima

Embodied Visual Learning with Kristen Grauman

Real-Time Machine Learning in the Database with Nikita Shamgunov

re:Invent Roundup Roundtable

Driving Customer Loyalty with Predictive and Conversational AI with Sherif Mityas

Innovations Factories for AI in Financial Services with Thierry Derungs

Block-Sparse Kernels for Deep Neural Networks with Durk Kingma

AI for Customer Service and Marketing at AeroMexico with Brian Gross

Scaling AI for the Enterprise with Mazin Gilbert

Scalable Distributed Deep Learning with Hillery Hunter

Robotics at OpenAI with Jonas Schneider

AI Robustness & Safety with Dario Amodei

Towards Artificial General Intelligence with Greg Brockman

Explaining Black Box Predictions with Sam Ritchie

Experimental Creative Writing with the Vectorized Word with Allison Parrish

The Biological Path Towards Strong AI with Matthew Taylor

Pytorch: Fast Differentiable Dynamic Graphs in Python with Soumith Chintala

Accessible Machine Learning for the Enterprise Developer with Ryan Sevey and Jason Montgomery

Bridging the Gap Between Academic and Industry Careers with Ross Fadely

The Limitations of Human-in-the-Loop AI with Dennis Mortensen

Nexus Lab Cohort 2 – Second Mind

Nexus Lab Cohort 2 – Bite.ai

Nexus Lab Cohort 2 – Bowtie

Nexus Lab Cohort 2 – Mt. Cleverest

Learning to Learn, and other Opportunities in Machine Learning with Graham Taylor

Building Conversational Applications for Financial Services with Kenneth Conroy

Fighting Fraud with Machine Learning at Shopify with Solmaz Shahalizadeh

Modeling Human Drivers for Autonomous Driving with Katie Driggs-Campbell

Perception Models for Self-Driving Cars with Jianxiong Xiao

Training Data for Autonomous Vehicles with Daryn Nakhuda

Human Factors in Machine Intelligence with James Guszcza

Intel Nervana Devcloud with Naveen Rao & Scott Apeland

AI-Powered Conversational Interfaces with Paul Tepper

Topological Data Analysis with Gunnar Carlsson

ML Use Cases at Think Big Analytics with Mo Patel and Laura Frølich

Ray: A Distributed Computing Platform for Reinforcement Learning with Ion Stoica

Bayesian Optimization for Hyperparameter Tuning with Scott Clark

Symbolic and Sub-Symbolic Natural Language Processing with Jonathan Mugan

Word2Vec & Friends with Bruno Goncalves

Evolutionary Algorithms in Machine Learning with Risto Miikkulainen

Agile Machine Learning at Walmart with Jennifer Prendki

LSTM’s, plus a Deep Learning History Lesson with Jürgen Schmidhuber

Machine Teaching for Better Machine Learning with Mark Hammond

Marrying Physics-Based and Data Driven ML Models with Josh Bloom

Cognitive Biases in Data Science with Drew Conway