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07/20/2023
Applying QNLP to sentiment analysis in finance
As an application domain where the slightest qualitative improvements ca...
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06/28/2023
Improving Primate Sounds Classification using Binary Presorting for Deep Learning
In the field of wildlife observation and conservation, approaches involv...
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06/09/2023
Weight Re-Mapping for Variational Quantum Algorithms
Inspired by the remarkable success of artificial neural networks across ...
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04/26/2023
CROP: Towards Distributional-Shift Robust Reinforcement Learning using Compact Reshaped Observation Processing
The safe application of reinforcement learning (RL) requires generalizat...
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01/18/2023
DIRECT: Learning from Sparse and Shifting Rewards using Discriminative Reward Co-Training
We propose discriminative reward co-training (DIRECT) as an extension to...
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01/18/2023
Compression of GPS Trajectories using Autoencoders
The ubiquitous availability of mobile devices capable of location tracki...
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01/06/2023
SEQUENT: Towards Traceable Quantum Machine Learning using Sequential Quantum Enhanced Training
Applying new computing paradigms like quantum computing to the field of ...
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01/04/2023
Attention-Based Recurrence for Multi-Agent Reinforcement Learning under State Uncertainty
State uncertainty poses a major challenge for decentralized coordination...
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12/20/2022
Visual Transformers for Primates Classification and Covid Detection
We apply the vision transformer, a deep machine learning model build aro...
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12/20/2022
Constructing Organism Networks from Collaborative Self-Replicators
We introduce organism networks, which function like a single neural netw...
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12/20/2022
Empirical Analysis of Limits for Memory Distance in Recurrent Neural Networks
Common to all different kinds of recurrent neural networks (RNNs) is the...
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12/20/2022
VoronoiPatches: Evaluating A New Data Augmentation Method
Overfitting is a problem in Convolutional Neural Networks (CNN) that cau...
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08/10/2022
Capturing Dependencies within Machine Learning via a Formal Process Model
The development of Machine Learning (ML) models is more than just a spec...
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07/15/2022
Stochastic Market Games
Some of the most relevant future applications of multi-agent systems lik...
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06/24/2022
Black Box Optimization Using QUBO and the Cross Entropy Method
Black box optimization (BBO) can be used to optimize functions whose ana...
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06/12/2022
Case-Based Inverse Reinforcement Learning Using Temporal Coherence
Providing expert trajectories in the context of Imitation Learning is of...
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04/28/2022
Algorithmic QUBO Formulations for k-SAT and Hamiltonian Cycles
Quadratic unconstrained binary optimization (QUBO) can be seen as a gene...
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12/14/2021
Quantifying Multimodality in World Models
Model-based Deep Reinforcement Learning (RL) assumes the availability of...
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12/14/2020
SAT-MARL: Specification Aware Training in Multi-Agent Reinforcement Learning
A characteristic of reinforcement learning is the ability to develop unf...
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12/11/2020
Acoustic Leak Detection in Water Networks
In this work, we present a general procedure for acoustic leak detection...
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08/11/2020
Surgical Mask Detection with Convolutional Neural Networks and Data Augmentations on Spectrograms
In many fields of research, labeled datasets are hard to acquire. This i...
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07/15/2020
Content-based Recommendations for Radio Stations with Deep Learned Audio Fingerprints
The world of linear radio broadcasting is characterized by a wide variet...
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06/05/2020
Acoustic Anomaly Detection for Machine Sounds based on Image Transfer Learning
In industrial applications, the early detection of malfunctioning factor...
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05/25/2020
Policy Entropy for Out-of-Distribution Classification
One critical prerequisite for the deployment of reinforcement learning s...
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04/29/2020
Insights on Training Neural Networks for QUBO Tasks
Current hardware limitations restrict the potential when solving quadrat...
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04/29/2020
The Holy Grail of Quantum Artificial Intelligence: Major Challenges in Accelerating the Machine Learning Pipeline
We discuss the synergetic connection between quantum computing and artif...
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03/30/2020
Optimizing Geometry Compression using Quantum Annealing
The compression of geometry data is an important aspect of bandwidth-eff...
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12/31/2019
Uncertainty-Based Out-of-Distribution Classification in Deep Reinforcement Learning
Robustness to out-of-distribution (OOD) data is an important goal in bui...
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08/05/2019
Difficulty Classification of Mountainbike Downhill Trails utilizing Deep Neural Networks
The difficulty of mountainbike downhill trails is a subjective perceptio...
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07/30/2019
Soccer Team Vectors
In this work we present STEVE - Soccer TEam VEctors, a principled approa...
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07/11/2019
Adaptive Thompson Sampling Stacks for Memory Bounded Open-Loop Planning
We propose Stable Yet Memory Bounded Open-Loop (SYMBOL) planning, a gene...
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05/10/2019
Emergent Escape-based Flocking Behavior using Multi-Agent Reinforcement Learning
In nature, flocking or swarm behavior is observed in many species as it ...
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05/10/2019
Memory Bounded Open-Loop Planning in Large POMDPs using Thompson Sampling
State-of-the-art approaches to partially observable planning like POMCP ...
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03/15/2019
A Quantum Annealing Algorithm for Finding Pure Nash Equilibria in Graphical Games
We introduce Q-Nash, a quantum annealing algorithm for the NP-complete p...
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02/13/2019
Assessing Solution Quality of 3SAT on a Quantum Annealing Platform
When solving propositional logic satisfiability (specifically 3SAT) usin...
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01/25/2019
Distributed Policy Iteration for Scalable Approximation of Cooperative Multi-Agent Policies
Decision making in multi-agent systems (MAS) is a great challenge due to...
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01/08/2019
Uncertainty-Based Out-of-Distribution Detection in Deep Reinforcement Learning
We consider the problem of detecting out-of-distribution (OOD) samples i...
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10/30/2018
Inheritance-Based Diversity Measures for Explicit Convergence Control in Evolutionary Algorithms
Diversity is an important factor in evolutionary algorithms to prevent p...
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03/07/2017