Lars Schmidt-Thieme

ORCID

Publication Activity (10 Years)

Years Active: 2001-2024
Publications (10 Years): 141

Top Venues

Karlsruhe Institute of Technology (PHD)

Education History

Karlsruhe Institute of Technology

PHD

Publications

Johannes Burchert, Thorben Werner, Vijaya Krishna Yalavarthi, Diego Coello de Portugal, Maximilian Stubbemann, Lars Schmidt-Thieme
Are EEG Sequences Time Series? EEG Classification with Time Series Models and Joint Subject Training. CoRR (2024)
Nourhan Ahmed, Lars Schmidt-Thieme
Structure-aware decoupled imputation network for multivariate time series. Data Min. Knowl. Discov. 38 (3) (2024)
Vijaya Krishna Yalavarthi, Kiran Madhusudhanan, Randolf Scholz, Nourhan Ahmed, Johannes Burchert, Shayan Jawed, Stefan Born, Lars Schmidt-Thieme
GraFITi: Graphs for Forecasting Irregularly Sampled Time Series. AAAI (2024)
Shereen Elsayed, Ahmed Rashed, Lars Schmidt-Thieme
HMAR: Hierarchical Masked Attention for Multi-Behaviour Recommendation. CoRR (2024)
Christian Klötergens, Vijaya Krishna Yalavarthi, Maximilian Stubbemann, Lars Schmidt-Thieme
Functional Latent Dynamics for Irregularly Sampled Time Series Forecasting. CoRR (2024)
Tim Dernedde, Daniela Thyssens, Sören Dittrich, Maximilan Stubbemann, Lars Schmidt-Thieme
Moco: A Learnable Meta Optimizer for Combinatorial Optimization. CoRR (2024)
Kiran Madhusudhanan, Shayan Jawed, Lars Schmidt-Thieme
Hyperparameter Tuning MLPs for Probabilistic Time Series Forecasting. CoRR (2024)
Nourhan Ahmed, Ahmed Rashed, Lars Schmidt-Thieme
Learning attentive attribute-aware node embeddings in dynamic environments. Int. J. Data Sci. Anal. 17 (2) (2024)
Kiran Madhusudhanan, Shayan Jawed, Lars Schmidt-Thieme
Hyperparameter Tuning MLP's for Probabilistic Time Series Forecasting. PAKDD (6) (2024)
Vijaya Krishna Yalavarthi, Randolf Scholz, Stefan Born, Lars Schmidt-Thieme
Probabilistic Forecasting of Irregular Time Series via Conditional Flows. CoRR (2024)
Shereen Elsayed, Ahmed Rashed, Lars Schmidt-Thieme
HMAR: Hierarchical Masked Attention for Multi-behaviour Recommendation. PAKDD (5) (2024)
Kiran Madhusudhanan, Gunnar Behrens, Maximilian Stubbemann, Lars Schmidt-Thieme
ProbSAINT: Probabilistic Tabular Regression for Used Car Pricing. CoRR (2024)
Vijaya Krishna Yalavarthi, Randolf Scholz, Kiran Madhusudhanan, Stefan Born, Lars Schmidt-Thieme
Marginalization Consistent Mixture of Separable Flows for Probabilistic Irregular Time Series Forecasting. CoRR (2024)
Shayan Jawed, Kiran Madhusudhanan, Vijaya Krishna Yalavarthi, Lars Schmidt-Thieme
Forecasting Early with Meta Learning. CoRR (2023)
Shereen Elsayed, Lars Schmidt-Thieme
Deep Multi-Representation Model for Click-Through Rate Prediction. IJCNN (2023)
Jonas K. Falkner, Lars Schmidt-Thieme
Too Big, so Fail? - Enabling Neural Construction Methods to Solve Large-Scale Routing Problems. CoRR (2023)
Nourhan Ahmed, Lars Schmidt-Thieme
Sparse self-attention guided generative adversarial networks for time-series generation. Int. J. Data Sci. Anal. 16 (4) (2023)
Vijaya Krishna Yalavarthi, Kiran Madusudanan, Randolf Scholz, Nourhan Ahmed, Johannes Burchert, Shayan Jawed, Stefan Born, Lars Schmidt-Thieme
Forecasting Irregularly Sampled Time Series using Graphs. CoRR (2023)
Mofassir ul Islam Arif, Johannes Burchert, Lars Schmidt-Thieme
ConvMix: Combining Intermediate Latent Features in Deep Convolutional Neural Networks. SCIA (2) (2023)
Thorben Werner, Johannes Burchert, Lars Schmidt-Thieme
Towards Comparable Active Learning. CoRR (2023)
Jonas K. Falkner, Lars Schmidt-Thieme
Neural Capacitated Clustering. IJCAI (2023)
Mofassir ul Islam Arif, Mohsan Jameel, Lars Schmidt-Thieme
Directly Optimizing IoU for Bounding Box Localization. CoRR (2023)
Nourhan Ahmed, Lars Schmidt-Thieme
Sparse Self-Attention Guided Generative Adversarial Networks for Time-Series Generation. DSAA (2023)
Rafael Rêgo Drumond, Lukas Brinkmeyer, Lars Schmidt-Thieme
Few-Shot Human Motion Prediction for Heterogeneous Sensors. PAKDD (2) (2023)
Christian Löwens, Daniela Thyssens, Emma Andersson, Christina Jenkins, Lars Schmidt-Thieme
DeepStay: Stay Region Extraction from Location Trajectories using Weak Supervision. CoRR (2023)
Shayan Jawed, Jan Stening, Lars Schmidt-Thieme
Pricing Used Vehicles at Volkswagen Financial Services AG. BigData (2023)
Shayan Jawed, Kiran Madhusudhanan, Vijaya Krishna Yalavarthi, Lars Schmidt-Thieme
Forecasting Early with Meta Learning. IJCNN (2023)
Daniela Thyssens, Tim Dernedde, Jonas K. Falkner, Lars Schmidt-Thieme
Routing Arena: A Benchmark Suite for Neural Routing Solvers. CoRR (2023)
Shereen Elsayed, Ahmed Rashed, Lars Schmidt-Thieme
Context-Aware Sequential Model for Multi-Behaviour Recommendation. CoRR (2023)
Mofassir ul Islam Arif, Mohsan Jameel, Josif Grabocka, Lars Schmidt-Thieme
Phantom Embeddings: Using Embedding Space for Model Regularization in Deep Neural Networks. CoRR (2023)
Vijaya Krishna Yalavarthi, Johannes Burchert, Lars Schmidt-Thieme
Tripletformer for Probabilistic Interpolation of Irregularly sampled Time Series. BigData (2023)
Jonas K. Falkner, Lars Schmidt-Thieme
Neural Capacitated Clustering. CoRR (2023)
Christian Löwens, Daniela Thyssens, Emma Andersson, Christina Jenkins, Lars Schmidt-Thieme
DeepStay: Stay Region Extraction from Location Trajectories Using Weak Supervision. ITSC (2023)
Mesay Samuel Gondere, Lars Schmidt-Thieme, Durga Prasad Sharma, Abiot Sinamo Boltena, Abey Bruck
Offline Handwritten Amharic Character Recognition Using Few-shot Learning. CoRR (2022)
Mesay Samuel Gondere, Lars Schmidt-Thieme, Durga Prasad Sharma, Abiot Sinamo Boltena
Improving Amharic Handwritten Word Recognition Using Auxiliary Task. CoRR (2022)
Daniela Thyssens, Jonas K. Falkner, Lars Schmidt-Thieme
Supervised Permutation Invariant Networks for Solving the CVRP with Bounded Fleet Size. CoRR (2022)
Christian Löwens, Inaam Ashraf, Alexander Gembus, Genesis Cuizon, Jonas K. Falkner, Lars Schmidt-Thieme
Solving the Traveling Salesperson Problem with Precedence Constraints by Deep Reinforcement Learning. KI (2022)
Vijaya Krishna Yalavarthi, Johannes Burchert, Lars Schmidt-Thieme
DCSF: Deep Convolutional Set Functions for Classification of Asynchronous Time Series. CoRR (2022)
Ahmad Bdeir, Jonas K. Falkner, Lars Schmidt-Thieme
Attention, Filling in The Gaps for Generalization in Routing Problems. CoRR (2022)
Christian Löwens, Inaam Ashraf, Alexander Gembus, Genesis Cuizon, Jonas K. Falkner, Lars Schmidt-Thieme
Solving the Traveling Salesperson Problem with Precedence Constraints by Deep Reinforcement Learning. CoRR (2022)
Mesay Samuel Gondere, Lars Schmidt-Thieme, Durga Prasad Sharma, Randolf Scholz
Multi-script handwritten digit recognition using multi-task learning. J. Intell. Fuzzy Syst. 43 (1) (2022)
Ekrem Öztürk, Fabio Ferreira, Hadi S. Jomaa, Lars Schmidt-Thieme, Josif Grabocka, Frank Hutter
Zero-Shot AutoML with Pretrained Models. CoRR (2022)
Kiran Madhusudhanan, Johannes Burchert, Nghia Duong-Trung, Stefan Born, Lars Schmidt-Thieme
U-Net Inspired Transformer Architecture for Far Horizon Time Series Forecasting. ECML/PKDD (6) (2022)
Lukas Brinkmeyer, Rafael Rêgo Drumond, Johannes Burchert, Lars Schmidt-Thieme
Few-Shot Forecasting of Time-Series with Heterogeneous Channels. ECML/PKDD (6) (2022)
Jonas K. Falkner, Daniela Thyssens, Ahmad Bdeir, Lars Schmidt-Thieme
Learning to Control Local Search for Combinatorial Optimization. ECML/PKDD (5) (2022)
Mesay Samuel Samuel, Lars Schmidt-Thieme, Durga Prasad Sharma, Abiot Sinamo Boltena, Abey Bruck
Offline Handwritten Amharic Character Recognition Using Few-Shot Learning. PanAfriCon AI (2022)
Tolga Akar, Thorben Werner, Vijaya Krishna Yalavarthi, Lars Schmidt-Thieme
Open Set Recognition for Time Series Classification. PAKDD (2) (2022)
Shayan Jawed, Mofassir ul Islam Arif, Ahmed Rashed, Kiran Madhusudhanan, Shereen Elsayed, Mohsan Jameel, Alexei Volk, Andre Hintsches, Marlies Kornfeld, Katrin Lange, Lars Schmidt-Thieme
A.I. and Data-Driven Mobility at Volkswagen Financial Services AG. CoRR (2022)
Rafael Rêgo Drumond, Lukas Brinkmeyer, Lars Schmidt-Thieme
Few-shot human motion prediction for heterogeneous sensors. CoRR (2022)
Ahmad Bdeir, Jonas K. Falkner, Lars Schmidt-Thieme
Attention, Filling in the Gaps for Generalization in Routing Problems. ECML/PKDD (6) (2022)
Daniel Pototzky, Azhar Sultan, Lars Schmidt-Thieme
Parting With Illusions About Synthetic Data. IVMSP (2022)
Shereen Elsayed, Lukas Brinkmeyer, Lars Schmidt-Thieme
End-to-End Image-Based Fashion Recommendation. CoRR (2022)
Jonas Schnepf, Paula Vetter, Tarik Temel, Bernd Scheuermann, Lars Schmidt-Thieme
On the Potential of Using ERP Business and System Data for Fraud Detection. Big Data (2022)
Jonas Sonntag, Gunnar Behrens, Lars Schmidt-Thieme
Positive-Unlabeled Domain Adaptation. DSAA (2022)
Shayan Jawed, Lars Schmidt-Thieme
Auxiliary Quantile Forecasting with Linear Networks. CoRR (2022)
Shereen Elsayed, Lars Schmidt-Thieme
Deep Multi-Representation Model for Click-Through Rate Prediction. CoRR (2022)
Jonas K. Falkner, Daniela Thyssens, Ahmad Bdeir, Lars Schmidt-Thieme
Learning to Control Local Search for Combinatorial Optimization. CoRR (2022)
Daniel Pototzky, Azhar Sultan, Lars Schmidt-Thieme
Does Self-Supervised Pretraining Really Match ImageNet Weights? IVMSP (2022)
Jonas K. Falkner, Daniela Thyssens, Lars Schmidt-Thieme
Large Neighborhood Search based on Neural Construction Heuristics. CoRR (2022)
Marta Kipke, Lukas Brinkmeyer, Souaybou Bagayoko, Lars Schmidt-Thieme, Martin Langner
Deep Level Annotation for Painter Attribution on Greek Vases utilizing Object Detection. SUMAC @ ACM Multimedia (2022)
Jonas Sonntag, Gunnar Behrens, Lars Schmidt-Thieme
Positive-Unlabeled Domain Adaptation. CoRR (2022)
Shayan Jawed, Lars Schmidt-Thieme
GQFormer: A Multi-Quantile Generative Transformer for Time Series Forecasting. Big Data (2022)
Ahmed Rashed, Shereen Elsayed, Lars Schmidt-Thieme
CARCA: Context and Attribute-Aware Next-Item Recommendation via Cross-Attention. CoRR (2022)
Vijaya Krishna Yalavarthi, Johannes Burchert, Lars Schmidt-Thieme
DCSF: Deep Convolutional Set Functions for Classification of Asynchronous Time Series. DSAA (2022)
Ahmed Rashed, Shereen Elsayed, Lars Schmidt-Thieme
Context and Attribute-Aware Sequential Recommendation via Cross-Attention. RecSys (2022)
Lukas Brinkmeyer, Rafael Rêgo Drumond, Johannes Burchert, Lars Schmidt-Thieme
Few-Shot Forecasting of Time-Series with Heterogeneous Channels. CoRR (2022)
Ekrem Öztürk, Fabio Ferreira, Hadi S. Jomaa, Lars Schmidt-Thieme, Josif Grabocka, Frank Hutter
Zero-shot AutoML with Pretrained Models. ICML (2022)
Nghia Duong-Trung, Stefan Born, Jong Woo Kim, Marie-Therese Schermeyer, Katharina Paulick, Maxim Borisyak, Ernesto Martinez, Mariano Nicolás Cruz Bournazou, Thorben Werner, Randolf Scholz, Lars Schmidt-Thieme, Peter Neubauer
When Bioprocess Engineering Meets Machine Learning: A Survey from the Perspective of Automated Bioprocess Development. CoRR (2022)
Daniel Pototzky, Azhar Sultan, Lars Schmidt-Thieme
FastSiam: Resource-Efficient Self-supervised Learning on a Single GPU. GCPR (2022)
Nghia Duong-Trung, Stefan Born, Kiran Madhusudhanan, Randolf Scholz, Johannes Burchert, Danh Le Phuoc, Lars Schmidt-Thieme
Put Attention to Temporal Saliency Patterns of Multi-Horizon Time Series. CoRR (2022)
Vijaya Krishna Yalavarthi, Johannes Burchert, Lars Schmidt-Thieme
Tripletformer for Probabilistic Interpolation of Asynchronous Time Series. CoRR (2022)
Hadi S. Jomaa, Lars Schmidt-Thieme, Josif Grabocka
Dataset2Vec: learning dataset meta-features. Data Min. Knowl. Discov. 35 (3) (2021)
Daniel Pototzky, Azhar Sultan, Matthias Kirschner, Lars Schmidt-Thieme
Self-supervised Learning for Object Detection in Autonomous Driving. GCPR (2021)
Sebastian Pineda-Arango, Felix Heinrich, Kiran Madhusudhanan, Lars Schmidt-Thieme
Multimodal Meta-Learning for Time Series Regression. AALTD@ECML/PKDD (2021)
Raaghav Radhakrishnan, Jan Fabian Schmid, Randolf Scholz, Lars Schmidt-Thieme
Deep Metric Learning for Ground Images. CoRR (2021)
Sebastian Pineda-Arango, Felix Heinrich, Kiran Madhusudhanan, Lars Schmidt-Thieme
Multimodal Meta-Learning for Time Series Regression. CoRR (2021)
Daniel Pototzky, Matthias Kirschner, Azhar Sultan, Lars Schmidt-Thieme
Training Object Detectors if Only Large Objects are Labeled. BMVC (2021)
Ahmad Bdeir, Simon Boeder, Tim Dernedde, Kirill Tkachuk, Jonas K. Falkner, Lars Schmidt-Thieme
RP-DQN: An application of Q-Learning to Vehicle Routing Problems. CoRR (2021)
Shereen Elsayed, Daniela Thyssens, Ahmed Rashed, Lars Schmidt-Thieme, Hadi Samer Jomaa
Do We Really Need Deep Learning Models for Time Series Forecasting? CoRR (2021)
Shayan Jawed, Hadi S. Jomaa, Lars Schmidt-Thieme, Josif Grabocka
Multi-task Learning Curve Forecasting Across Hyperparameter Configurations and Datasets. ECML/PKDD (1) (2021)
Ahmed Rashed, Josif Grabocka, Lars Schmidt-Thieme
A Guided Learning Approach for Item Recommendation via Surrogate Loss Learning. SIGIR (2021)
Kiran Madhusudhanan, Johannes Burchert, Nghia Duong-Trung, Stefan Born, Lars Schmidt-Thieme
Yformer: U-Net Inspired Transformer Architecture for Far Horizon Time Series Forecasting. CoRR (2021)
Jonas Sonntag, Michael Engel, Lars Schmidt-Thieme
Predicting Parking Availability from Mobile Payment Transactions with Positive Unlabeled Learning. AAAI (2021)
Hadi S. Jomaa, Lars Schmidt-Thieme, Josif Grabocka
Hyperparameter Optimization with Differentiable Metafeatures. CoRR (2021)
Daniel Pototzky, Matthias Kirschner, Lars Schmidt-Thieme
Leveraging Group Annotations in Object Detection Using Graph-Based Pseudo-labeling. GCPR (2021)
Mesay Samuel Gondere, Lars Schmidt-Thieme, Durga Prasad Sharma, Randolf Scholz
Multi-script Handwritten Digit Recognition Using Multi-task Learning. CoRR (2021)
Hadi S. Jomaa, Jonas K. Falkner, Lars Schmidt-Thieme
Improving Hyperparameter Optimization by Planning Ahead. CoRR (2021)
Ahmad Bdeir, Simon Boeder, Tim Dernedde, Kirill Tkachuk, Jonas K. Falkner, Lars Schmidt-Thieme
RP-DQN: An Application of Q-Learning to Vehicle Routing Problems. KI (2021)
Mohsan Jameel, Shayan Jawed, Lars Schmidt-Thieme
Optimal Topology Search for Fast Model Averaging in Decentralized Parallel SGD. PAKDD (2) (2020)
Jonas K. Falkner, Lars Schmidt-Thieme
Learning to Solve Vehicle Routing Problems with Time Windows through Joint Attention. CoRR (2020)
Shayan Jawed, Josif Grabocka, Lars Schmidt-Thieme
Self-supervised Learning for Semi-supervised Time Series Classification. PAKDD (1) (2020)
Rafael Rêgo Drumond, Lukas Brinkmeyer, Josif Grabocka, Lars Schmidt-Thieme
HIDRA: Head Initialization across Dynamic targets for Robust Architectures. SDM (2020)
Mofassir ul Islam Arif, Mohsan Jameel, Josif Grabocka, Lars Schmidt-Thieme
Phantom Embeddings: Using Embeddings Space for Model Regularization in Deep Neural Networks. LWDA (2020)
Ahmed Rashed, Shayan Jawed, Lars Schmidt-Thieme, Andre Hintsches
MultiRec: A Multi-Relational Approach for Unique Item Recommendation in Auction Systems. RecSys (2020)
Mohsan Jameel, Mofassir ul Islam Arif, Andre Hintsches, Lars Schmidt-Thieme
Automation of Leasing Vehicle Return Assessment Using Deep Learning Models. ECML/PKDD (4) (2020)
Jonas Sonntag, Lars Schmidt-Thieme
A machine learning approach to infer on-street parking occupancy based on parking meter transactions. ITSC (2020)
Riccardo Lucato, Jonas K. Falkner, Lars Schmidt-Thieme
An efficient evolutionary solution to the joint order batching - order picking planning problem. GECCO Companion (2020)
Ahmed Rashed, Shayan Jawed, Jens Rehberg, Josif Grabocka, Lars Schmidt-Thieme, Andre Hintsches
A Deep Multi-task Approach for Residual Value Forecasting. ECML/PKDD (3) (2019)
Shayan Jawed, Ahmed Rashed, Lars Schmidt-Thieme
Multi-step Forecasting via Multi-task Learning. IEEE BigData (2019)
Hadi S. Jomaa, Josif Grabocka, Lars Schmidt-Thieme
Dataset2Vec: Learning Dataset Meta-Features. CoRR (2019)

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Publication Activity (10 Years)

Top Topics

Top Venues

Lars Schmidt-Thieme