Multi-modal large language models (MLLMs) have enabled numerous advances in understanding and reasoning in domains like vision, but we have not yet seen this broad success for time-series. Although prior works on time-series MLLMs have shown promising performance in time-series forecasting, very few works show… Read More »Towards Time-Series Reasoning with LLMs Apple Machine Learning Research
Motivated by the phenomenon of strategic agents gaming a recommendation system to maximize the number of times they are recommended to users, we study a strategic variant of the linear contextual bandit problem, where the arms strategically misreport privately observed contexts to the learner. %… Read More »Strategic Linear Contextual Bandits Apple Machine Learning Research
[[{“value”:”*Equal Contributors Data from wearable sensors (e.g., heart rate, step count) can be used to model mood patterns. We characterize feature representations and modeling strategies with multi-modal discrete time series data for mood pattern classification with a large dataset with naturalistic missingness (n=116,819 participants) using… Read More »Leveraging Periodicity for Robustness with Multi-modal Mood Pattern Models Apple Machine Learning Research
Single-cell genomics has significantly advanced our understanding of cellular behavior, catalyzing innovations in treatments and precision medicine. However, single-cell sequencing technologies are inherently destructive and can only measure a limited array of data modalities simultaneously. This limitation underscores the need for new methods capable of… Read More »GENOT: Entropic (Gromov) Wasserstein Flow Matching with Applications to Single-Cell Genomics Apple Machine Learning Research
[[{“value”:”Given a source and a target probability measure supported on Rdmathbb{R}^dRd, the Monge problem aims for the most efficient way to map one distribution to the other. This efficiency is quantified by defining a cost function between source and target data. Such a cost is… Read More »Learning Elastic Costs to Shape Monge Displacements Apple Machine Learning Research
[[{“value”:” Cohere is a prominent company specializing in enterprise-focused artificial intelligence (AI) solutions. Located in Toronto, Canada, it has contributed significantly throughout 2024 with groundbreaking advancements. These developments span generative AI, multilingual processing, and enterprise-ready AI applications, reflecting Cohere’s focus on driving innovation and enhancing… Read More »Cohere Evolves Enterprise AI in 2024: Innovations in Generative Models, Multilingual Processing, and Developer Tools Sana Hassan Artificial Intelligence Category – MarkTechPost
[[{“value”:” Chronos-Bolt is the newest addition to AutoGluon-TimeSeries, delivering accurate zero-shot forecasting up to 250 times faster than the original Chronos models [1]. Time series forecasting plays a vital role in guiding key business decisions across industries such as retail, energy, finance, and healthcare. Traditionally,… Read More »Fast and accurate zero-shot forecasting with Chronos-Bolt and AutoGluon Abdul Fatir Ansari AWS Machine Learning Blog
[[{“value”:” Today, the Accounts Payable (AP) and Accounts Receivable (AR) analysts in Amazon Finance operations receive queries from customers through email, cases, internal tools, or phone. When a query arises, analysts must engage in a time-consuming process of reaching out to subject matter experts (SMEs)… Read More »How Amazon Finance Automation built a generative AI Q&A chat assistant using Amazon Bedrock Soheb Moin AWS Machine Learning Blog
[[{“value”:” Speech synthesis has become a transformative research area, focusing on creating natural and synchronized audio outputs from diverse inputs. Integrating text, video, and audio data provides a more comprehensive approach to mimic human-like communication. Advances in machine learning, particularly transformer-based architectures, have driven innovations,… Read More »Visatronic: A Unified Multimodal Transformer for Video-Text-to-Speech Synthesis with Superior Synchronization and Efficiency Nikhil Artificial Intelligence Category – MarkTechPost
[[{“value”:” Home Table of Contents Fine Tune PaliGemma with QLoRA for Visual Question Answering What Is PaliGemma? What Is a Vision-Language Model? Architecture of PaliGemma How Is PaliGemma Trained? Available Model Checkpoints Use Cases of PaliGemma Why PaliGemma? Inference with PaliGemma Setup and Imports Run… Read More »Fine Tune PaliGemma with QLoRA for Visual Question Answering Piyush Thakur PyImageSearch