2026-10-12 13:34 |
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2026-10-12 13:31 |
[FZJ-2026-04984]
Contribution to a conference proceedings
Neyaz, S. Y. ; Ashok, A. ; Schiek, M. ; et al
A 28 nm PLL-Based Oscillator Network for Synchronization and Oscillator-based Optimization
20262026 22nd International Conference on Synthesis, Modeling, Analysis and Simulation Methods, and Applications to Circuits Design (SMACD), DresdenDresden, Germany, 29 Jun 2026 - 2 Jul 20262026-06-292026-07-02
IEEE 1-4 (2026) [10.1109/SMACD70206.2026.11647793]2026
We present a coupled oscillator ASIC fabricated in 28 nm CMOS for high-speed exploration of synchronization dynamics and analog combinatorial optimization. Instead of relying on computationally intensive numerical simulations, the proposed architecture maps the Kuramoto phase interaction model onto the control dynamics of a cluster of third-order type-II Phase-Locked Loops (PLLs). [...]
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2026-10-12 13:28 |
[FZJ-2026-04983]
Contribution to a conference proceedings
Kuriakose, N. ; Ashok, A. ; Kusuma, S. ; et al
Memristor Conductance Control System-on-Chip Using Current Controlled Techniques in 28 nm CMOS Technology
20262026 22nd International Conference on Synthesis, Modeling, Analysis and Simulation Methods, and Applications to Circuits Design (SMACD), DresdenDresden, Germany, 29 Jun 2026 - 2 Jul 20262026-06-292026-07-02
IEEE 1-4 (2026) [10.1109/SMACD70206.2026.11647798]2026
Memristive devices are typically operated using voltage driven schemes with current compliance to regulate switching dynamics. While effective, this approach often leads to abrupt current overshoot and subsequent IR drops, excessive power dissipation, and limited precision in tuning intermediate conductance states. [...]
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2026-10-12 10:59 |
[FZJ-2026-04958]
Contribution to a conference proceedings/Contribution to a book
Matthews, P. ; Krieger, L. ; Amico, T. ; et al
ExDBSCAN: Explaining DBSCAN with Counterfactual Reasoning
2026Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2 KDD '26: The 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Jeju Island Republic of KoreaJeju Island Republic of Korea, South Korea, 9 Aug 2026 - 13 Aug 20262026-08-092026-08-13
ACM New York, NY, USA 3703 - 3714 (2026) [10.1145/3770855.3817692]2026
Clustering is an unsupervised technique for grouping data points by similarity. While explainability methods exist for supervised machine learning, they are not directly applicable to clustering, making it challenging to understand cluster assignments. [...]
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2026-10-12 10:53 |
[FZJ-2026-04957]
Contribution to a conference proceedings/Contribution to a book
Amico, T. ; Matthews, P. ; Krieger, L. ; et al
DCFO: Density-Based Counterfactuals for Outliers
2026Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining V. 1 ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Jeju Island Republic of KoreaJeju Island Republic of Korea, South Korea, 9 Aug 2026 - 13 Aug 20262026-08-092026-08-13
ACM New York, NY, USA 37-48 (2026) [10.1145/3770854.3780205]2026
Outlier detection identifies data points that significantly deviate from the majority of the data distribution. Explaining outliers is crucial for understanding the underlying factors that contribute to their detection, validating their significance, and identifying potential biases or errors. [...]
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2026-10-12 10:45 |
[FZJ-2026-04956]
Journal Article/Contribution to a conference proceedings/Contribution to a book
Zhao, X. ; Krieger, L. ; Cao, Z. ; et al
RECAST: Model Reconstruction via Counterfactual-Aware Wasserstein Geometry under Limited Data
2026Proceedings of the 43rd International Conference on Machine Learning International Conference on Machine Learning, SeoulSeoul, South Korea, 6 Jul 2026 - 11 Jul 20262026-07-062026-07-11
PMLR 306, 161567-161591 (2026)2026
Counterfactual explanations (CFs) help understand machine learning models by identifying minimal input changes that would lead to alternative model outcomes. Recent work demonstrates their utility for reconstructing black-box models, enabling third-party auditing of opaque decision systems for fairness and accountability. [...]
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2026-10-12 10:36 |
[FZJ-2026-04955]
Contribution to a conference proceedings/Contribution to a book
Beer, A. ; Krieger, L. ; Weber, P. ; et al
Internal Evaluation of Density-Based Clusterings with Noise
2026International Conference on Learning Representations International Conference on Learning Representations, Rio de JaneiroRio de Janeiro, Brazil, 23 Apr 2026 - 27 Apr 20262026-04-232026-04-27
2026, 86149-86172 (2026)2026
Evaluating the quality of a clustering result without access to ground truth labels is fundamental for research in data mining. However, most cluster validation indices (CVIs) do not consider the noise assignments by density-based clustering methods like DBSCAN or HDBSCAN, even though the ability to correctly determine noise is paramount to successful clustering. [...]
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2026-10-08 14:54 |
[FZJ-2026-04927]
Contribution to a conference proceedings
Steinbach ; Fomina, M. ; Haar, E. ; et al
Using flicker noise in Graphene Field-Effect Transistors for biosensing
2026The 26th International Conference on the Science and Applications of Nanotubes and Low-Dimensional Materials, NT26, BerlinBerlin, Germany, 23 Aug 2026 - 28 Aug 20262026-08-232026-08-28
176 pp. (2026)2026
Graphene-based field-effect transistors (GFETs) functionalized with lipid monolayers provide a controlled and label-free platform for studying membrane-associated proteins [1]. We have recently shown that the flicker noise of the device changes upon protein binding even when the charge-neutrality point remains at the same gate voltage [2]. [...]
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2026-10-06 13:56 |
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2026-10-02 15:29 |
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