Learning In-the-Wild Sensor Simulation for Autonomous Driving
Explore cutting-edge sensor simulation techniques for autonomous driving. Learn to create digital twins, manipulate scenarios, and generate realistic multi-sensor simulations to enhance self-driving vehicle development.
Cognitive Simulation: Combining Simulation and Experiment with Artificial Intelligence
Explore cognitive simulation techniques merging AI with experimental and simulation data for advanced scientific insights and predictive capabilities.
Leakage and the Reproducibility Crisis in ML-based Science
Explore data leakage and reproducibility issues in ML-based science. Learn about types of leakage, their impact on research, and proposed solutions for improving scientific reporting and methodology.
Calling the Shot: How AI Predicted Fusion Ignition Before It Happened
Explore how AI predicted fusion ignition at the National Ignition Facility, revolutionizing clean energy research and bringing us closer to harnessing the power of the stars.
Machine Learning Applications in Scientific Problems with Sparse Data - Afternoon Address
Explore Dr. Kelli Humbird's career in data science, focusing on inertial confinement fusion and machine learning applications in scientific problems with sparse data.
Guided Deep Learning Manifold Linearization of Porous Media Flow Equations for Digital Twins Operations
Explore advanced techniques in Digital Twin operations for reservoir management, focusing on physics-aware machine learning methods to enhance simulation accuracy and efficiency.
Ontologies, Graph Deep Learning, and AI in Materials Science
Explore ontologies, graph deep learning, and AI in materials science, focusing on advanced manufacturing and synchrotron science. Learn about innovative approaches for multimodal analysis and decision-making.
FOCUS Technique: Evolutionary Testing Simulation with Out-of-Distribution Images
Explorez les techniques d'essais évolutifs et de simulation avec des images hors distribution pour améliorer la robustesse des modèles d'apprentissage automatique.
Where Vector Search is Taking Us
Explore vector search options, components, and future prospects with industry expert Dmitry Kan in this keynote address from Haystack EU 2022.
Building an Open-Source Online Learn-to-Rank Engine - Haystack EU 2022
Explore Metarank, an open-source personalization service for learn-to-rank tasks. Discover how it simplifies data engineering challenges and improves search relevancy through visitor behavior analysis.
A Practical Approach to Measuring Relevance in E-commerce Search Engines
Implement a component to measure e-commerce search engine relevance using NDCG theory. Learn practical details, integration, and ROI for preventing relevance regressions.
Lowering the Entry Threshold for Neural Vector Search - Applying Similarity Learning
Explore similarity learning for efficient neural search implementation, reducing data requirements and training time while addressing domain-specific challenges.
Testing in Apache Solr - Session 3
Explore Solr's testing capabilities, learn to contribute effectively, and master techniques for writing and managing tests in Apache Solr.
Data Labeling for Search Relevance Evaluation
Explore data labeling techniques for search relevance evaluation, focusing on human-in-the-loop pipelines, ranking metrics, and crowdsourcing best practices.
Vectorize Your E-commerce Search
Discover how vector search enhances e-commerce, solving misspellings and boosting relevance. Learn about Chorus's new vector capabilities for improved search experiences.
Effective Relevancy Change Management in Search Systems
Explore effective search relevancy change management techniques for continuous improvement in search systems and feature engineering.
Relevance in the Age of Generative Search - Haystack US 2023 Keynote
Explore the integration of generative AI in search, covering strategies, code examples, and the balance between AI capabilities and traditional relevance techniques for accurate results.
Populating and Leveraging Semantic Knowledge Graphs to Supercharge Search
Populate and leverage semantic knowledge graphs to enhance search capabilities, enabling concept-based queries, query expansion, and improved long-tail query matching for reduced zero-result searches.
Exploiting Citation Networks in Large Corpora to Improve Relevance on Broad Queries
Discover how to leverage citation networks in large legal databases to improve search relevance for broad queries, enhancing user experience and document ranking accuracy.
Talking to Non-Searchers about Search Relevance - Haystack US 2023
Learn effective strategies for explaining search relevance to non-technical stakeholders, from CEOs to clients. Gain insights on communicating complex search concepts and their importance.
Breaking Search Performance Limits with Domain-Specific Computing
Explore advanced search techniques using domain-specific computing to achieve faster latencies and higher scalability at billion-scale, overcoming limitations of general-purpose CPUs.