Search Results for author: Philipp Singer

Found 8 papers, 5 papers with code

h2oGPT: Democratizing Large Language Models

2 code implementations13 Jun 2023 Arno Candel, Jon McKinney, Philipp Singer, Pascal Pfeiffer, Maximilian Jeblick, Prithvi Prabhu, Jeff Gambera, Mark Landry, Shivam Bansal, Ryan Chesler, Chun Ming Lee, Marcos V. Conde, Pasha Stetsenko, Olivier Grellier, SriSatish Ambati

Applications built on top of Large Language Models (LLMs) such as GPT-4 represent a revolution in AI due to their human-level capabilities in natural language processing.

Chatbot Fairness +8

Supporting large-scale image recognition with out-of-domain samples

1 code implementation4 Oct 2020 Christof Henkel, Philipp Singer

This article presents an efficient end-to-end method to perform instance-level recognition employed to the task of labeling and ranking landmark images.

Image Classification Image Retrieval +1

Recognizing bird species in diverse soundscapes under weak supervision

1 code implementation16 Jul 2021 Christof Henkel, Pascal Pfeiffer, Philipp Singer

We present a robust classification approach for avian vocalization in complex and diverse soundscapes, achieving second place in the BirdCLEF2021 challenge.

Robust classification

Backtesting the predictability of COVID-19

1 code implementation22 Jul 2020 Dmitry Gordeev, Philipp Singer, Marios Michailidis, Mathias Müller, SriSatish Ambati

Our work studies the predictive performance of models at various stages of the pandemic to better understand their fundamental uncertainty and the impact of data availability on such forecasts.

Discovering Beaten Paths in Collaborative Ontology-Engineering Projects using Markov Chains

no code implementations8 Jul 2014 Simon Walk, Philipp Singer, Markus Strohmaier, Tania Tudorache, Mark A. Musen, Natalya F. Noy

For example, the 11th revision of the ICD, which is currently under active development by the WHO contains nearly 50, 000 classes representing a vast variety of different diseases and causes of death.

Discovering and Characterizing Mobility Patterns in Urban Spaces: A Study of Manhattan Taxi Data

no code implementations20 Jan 2016 Lisette Espín-Noboa, Florian Lemmerich, Philipp Singer, Markus Strohmaier

By applying this combination of approaches to taxi data in Manhattan, we can discover and explain different patterns in human mobility that cannot be identified in a collective analysis.

Recommendation Systems

H2O-Danube-1.8B Technical Report

no code implementations30 Jan 2024 Philipp Singer, Pascal Pfeiffer, Yauhen Babakhin, Maximilian Jeblick, Nischay Dhankhar, Gabor Fodor, Sri Satish Ambati

We present H2O-Danube-1. 8B, a 1. 8B language model trained on 1T tokens following the core principles of LLama 2 and Mistral.

Language Modelling

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