· ai
[Paper] BEDS: Bayesian Emergent Dissipative Structures
We present BEDS (Bayesian Emergent Dissipative Structures), a theoretical framework that unifies concepts from non-equilibrium thermodynamics, Bayesian inferenc...
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[Paper] Hunting for 'Oddballs' with Machine Learning: Detecting Anomalous Exoplanets Using a Deep-Learned Low-Dimensional Representation of Transit Spectra with Autoencoders
This study explores the application of autoencoder-based machine learning techniques for anomaly detection to identify exoplanet atmospheres with unconventional...
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[Paper] Environment-Adaptive Covariate Selection: Learning When to Use Spurious Correlations for Out-of-Distribution Prediction
Out-of-distribution (OOD) prediction is often approached by restricting models to causal or invariant covariates, avoiding non-causal spurious associations that...
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[Paper] Estimating Text Temperature
Autoregressive language models typically use temperature parameter at inference to shape the probability distribution and control the randomness of the text gen...
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[Paper] Fusion2Print: Deep Flash-Non-Flash Fusion for Contactless Fingerprint Matching
Contactless fingerprint recognition offers a hygienic and convenient alternative to contact-based systems, enabling rapid acquisition without latent prints, pre...
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[Paper] DatBench: Discriminative, Faithful, and Efficient VLM Evaluations
Empirical evaluation serves as the primary compass guiding research progress in foundation models. Despite a large body of work focused on training frontier vis...
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[Paper] Prithvi-Complimentary Adaptive Fusion Encoder (CAFE): unlocking full-potential for flood inundation mapping
Geo-Foundation Models (GFMs), have proven effective in diverse downstream applications, including semantic segmentation, classification, and regression tasks. H...
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[Paper] Project Ariadne: A Structural Causal Framework for Auditing Faithfulness in LLM Agents
As Large Language Model (LLM) agents are increasingly tasked with high-stakes autonomous decision-making, the transparency of their reasoning processes has beco...
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[Paper] Game of Coding: Coding Theory in the Presence of Rational Adversaries, Motivated by Decentralized Machine Learning
Coding theory plays a crucial role in enabling reliable communication, storage, and computation. Classical approaches assume a worst-case adversarial model and ...
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[Paper] Placement Semantics for Distributed Deep Learning: A Systematic Framework for Analyzing Parallelism Strategies
Training large language models requires distributing computation across many accelerators, yet practitioners select parallelism strategies (data, tensor, pipeli...
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[Paper] Temporal Kolmogorov-Arnold Networks (T-KAN) for High-Frequency Limit Order Book Forecasting: Efficiency, Interpretability, and Alpha Decay
High-Frequency trading (HFT) environments are characterised by large volumes of limit order book (LOB) data, which is notoriously noisy and non-linear. Alpha de...
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[Paper] 360DVO: Deep Visual Odometry for Monocular 360-Degree Camera
Monocular omnidirectional visual odometry (OVO) systems leverage 360-degree cameras to overcome field-of-view limitations of perspective VO systems. However, ex...