156 citations · 201 across the 12 of their papers we have counts for
12 papers
The Amazon Nova Family of Models: Technical Report and Model Card
Amazon AGI, Aaron Langford, Aayush Shah +783
We present Amazon Nova, a new generation of state-of-the-art foundation models that deliver frontier intelligence and industry-leading price performance. Amazon Nova Pro is a highl…
Manifold Restricted Interventional Shapley Values
Muhammad Faaiz Taufiq, Patrick Blöbaum, Lenon Minorics
Shapley values are model-agnostic methods for explaining model predictions. Many commonly used methods of computing Shapley values, known as off-manifold methods, rely on model eva…
Unsupervised Model Selection for Time-series Anomaly Detection
Mononito Goswami, Cristian Challu, Laurent Callot +2
Anomaly detection in time-series has a wide range of practical applications. While numerous anomaly detection methods have been proposed in the literature, a recent survey conclude…
Testing Granger Non-Causality in Panels with Cross-Sectional Dependencies
Lenon Minorics, Caner Turkmen, David Kernert +3
This paper proposes a new approach for testing Granger non-causality on panel data. Instead of aggregating panel member statistics, we aggregate their corresponding p-values and sh…
Correcting Confounding via Random Selection of Background Variables
You-Lin Chen, Lenon Minorics, Dominik Janzing
We propose a method to distinguish causal influence from hidden confounding in the following scenario: given a target variable Y, potential causal drivers X, and a large number of…
Causal Forecasting:Generalization Bounds for Autoregressive Models
Leena Chennuru Vankadara, Philipp Michael Faller, Michaela Hardt +3
Despite the increasing relevance of forecasting methods, causal implications of these algorithms remain largely unexplored. This is concerning considering that, even under simplify…
Quantifying intrinsic causal contributions via structure preserving interventions
Dominik Janzing, Patrick Blöbaum, Atalanti A. Mastakouri +3
We propose a notion of causal influence that describes the `intrinsic' part of the contribution of a node on a target node in a DAG. By recursively writing each node as a function…
Causal structure based root cause analysis of outliers
Dominik Janzing, Kailash Budhathoki, Lenon Minorics +1
We describe a formal approach to identify 'root causes' of outliers observed in variables in a scenario where the causal relation between the variables is a kno…
Feature relevance quantification in explainable AI: A causal problem
Dominik Janzing, Lenon Minorics, Patrick Blöbaum
We discuss promising recent contributions on quantifying feature relevance using Shapley values, where we observed some confusion on which probability distribution is the right one…
Eigenvalue Approximation for Krein-Feller-Operators
Uta Freiberg, Lenon Minorics
We study the limiting behavior of the eigenvalues of Krein-Feller-Operators with respect to weakly convergent probability measures. Therefore, we give a representation of the eigen…
Spectral Asymptotics for Krein-Feller-Operators with respect to -Variable Cantor Measures
Lenon Alexander Minorics
We study the limiting behavior of the Dirichlet and Neumann eigenvalue counting function of generalized second order differential operators , where …
Spectral Asymptotics for Krein-Feller-Operators with respect to Random Recursive Cantor Measures
Lenon Minorics
We study the limit behavior of the Dirichlet and Neumann eigenvalue counting function of generalized second order differential operators , where is…