Scientific Inference

Scientific inference, the process of drawing conclusions from data, is a core challenge across numerous scientific fields, with current research focusing on improving efficiency and accuracy. This involves developing novel algorithms and architectures, such as those based on Bayesian networks, diffusion transformers, and autoregressive models, to optimize inference processes in various contexts, including large language models and image processing. These advancements are crucial for accelerating scientific discovery and enabling real-world applications in areas like personalized medicine, legal tech, and industrial automation, where efficient and reliable inference is paramount. The emphasis is on addressing computational bottlenecks and improving the reliability of inferences, particularly in scenarios with limited data or complex models.

Papers

October 4, 2023

Online Estimation and Inference for Robust Policy Evaluation in Reinforcement Learning
Weidong Liu, Jiyuan Tu, Yichen Zhang, Xi Chen
Reinforcement Learning Scientific Inference Online Estimation Robust Statistic Heavy Tailed Reward Robust Policy Evaluation

October 3, 2023

FLEDGE: Ledger-based Federated Learning Resilient to Inference and Backdoor Attacks
Jorge Castillo, Phillip Rieger, Hossein Fereidooni, Qian Chen, Ahmad Sadeghi
Differential Privacy Federated Learning Backdoor Attack Scientific Inference Reward Function Secure Multi Party Computation

October 1, 2023

September 29, 2023

September 25, 2023

September 21, 2023

Optimal Conditional Inference in Adaptive Experiments
Jiafeng Chen, Isaiah Andrews
Scientific Inference Conditional Distribution Adaptive Experiment Bandit Model

September 20, 2023

Colour Passing Revisited: Lifted Model Construction with Commutative Factors
Malte Luttermann, Tanya Braun, Ralf Möller, Marcel Gehrke
Scientific Inference Inference Algorithm Lifted Inference Tractable Probabilistic Inference Probabilistic Inference Exploit Symmetry

September 19, 2023

An Extendable Python Implementation of Robust Optimisation Monte Carlo
Vasilis Gkolemis, Michael Gutmann, Henri Pesonen
Scientific Inference Python Library Intractable Likelihood Likelihood Free Inference Robust Optimisation

September 17, 2023

Data-driven Modeling and Inference for Bayesian Gaussian Process ODEs via Double Normalizing Flows
Jian Xu, Shian Du, Junmei Yang, Xinghao Ding, John Paisley, Delu Zeng
Gaussian Process Scientific Inference Normalizing Flow Posterior Inference Data Driven Modeling Probability Flow ODE

September 11, 2023

Memory Injections: Correcting Multi-Hop Reasoning Failures during Inference in Transformer-Based Language Models
Mansi Sakarvadia, Aswathy Ajith, Arham Khan, Daniel Grzenda, Nathaniel Hudson, André Bauer, Kyle Chard, Ian Foster
Scientific Inference Transformer Based Language Model Multi Hop Reasoning Multi Hop Question

September 5, 2023

PolyLUT: Learning Piecewise Polynomials for Ultra-Low Latency FPGA LUT-based Inference
Marta Andronic, George A. Constantinides
Scientific Inference Field Programmable Gate Array DNN Inference Deep Learning Inference

September 3, 2023

Towards Efficient Modeling and Inference in Multi-Dimensional Gaussian Process State-Space Models
Zhidi Lin, Juan Maroñas, Ying Li, Feng Yin, Sergios Theodoridis
Gaussian Process Scientific Inference State Space Model State Space Latent State Efficient Model Latent Dimension Gaussian Process State Space Model

August 31, 2023

Joint Semantic-Native Communication and Inference via Minimal Simplicial Structures
Qiyang Zhao, Hang Zou, Mehdi Bennis, Merouane Debbah, Ebtesam Almazrouei, Faouzi Bader
Scientific Inference Semantic Communication Simplicial Complex Simplicial Convolutional

August 29, 2023

August 19, 2023

Scientific Inference

Papers

Online Estimation and Inference for Robust Policy Evaluation in Reinforcement Learning

FLEDGE: Ledger-based Federated Learning Resilient to Inference and Backdoor Attacks

A Framework for Inference Inspired by Human Memory Mechanisms

Statistical Limits of Adaptive Linear Models: Low-Dimensional Estimation and Inference

Estimation and Inference in Distributional Reinforcement Learning

Training and inference of large language models using 8-bit floating point

Physics of Language Models: Part 3.2, Knowledge Manipulation

Learning to Abstain From Uninformative Data

Optimal Conditional Inference in Adaptive Experiments

Colour Passing Revisited: Lifted Model Construction with Commutative Factors

An Extendable Python Implementation of Robust Optimisation Monte Carlo

Data-driven Modeling and Inference for Bayesian Gaussian Process ODEs via Double Normalizing Flows

Memory Injections: Correcting Multi-Hop Reasoning Failures during Inference in Transformer-Based Language Models

PolyLUT: Learning Piecewise Polynomials for Ultra-Low Latency FPGA LUT-based Inference

Towards Efficient Modeling and Inference in Multi-Dimensional Gaussian Process State-Space Models

Joint Semantic-Native Communication and Inference via Minimal Simplicial Structures

Multi-Response Heteroscedastic Gaussian Process Models and Their Inference

Cross-Modal Retrieval Meets Inference:Improving Zero-Shot Classification with Cross-Modal Retrieval

Towards Probabilistic Causal Discovery, Inference & Explanations for Autonomous Drones in Mine Surveying Tasks

East: Efficient and Accurate Secure Transformer Framework for Inference