First O-Glycosylation from Unprotected 1-Thioimidoyl Hexofuranosides Assisted by Divalent Cations

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Beliefs inform the behaviour of forward-thinking agents in complex environments. Recently, sequential Bayesian inference has emerged as a mechanism to study belief formation among agents adapting to dynamical conditions. However, we lack critical theory to ...

Proteins and lipids decorated with glycans are found throughout biological entities, playing roles in biological functions and dysfunctions. Current analytical strategies for these glycan-decorated biomolecules, termed glycoconjugates, rely on ensemble-ave ...

Glycans play an essential role in numerous physiological and pathological processes of living organisms. Despite their significant biological relevance, glycobiology remains one of the least explored fields of biochemistry. The intrinsic isomeric complexit ...

A multi-agent system consists of a collection of decision-making or learning agents subjected to streaming observations from some real-world phenomenon. The goal of the system is to solve some global learning or optimization problem in a distributed or dec ...

This article reviews significant advances in networked signal and information processing (SIP), which have enabled in the last 25 years extending decision making and inference, optimization, control, and learning to the increasingly ubiquitous environments ...

In multi-agent reinforcement learning, multiple agents learn simultaneously while interacting with a common environment and each other. Since the agents adapt their policies during learning, not only the behavior of a single agent becomes non-stationary, b ...

This paper considers the problem of resilient distributed optimization and stochastic learning in a server-based architecture. The system comprises a server and multiple agents, where each agent has its own local cost function. The agents collaborate with ...

This work addresses the problem of sharing partial information within social learning strategies. In social learning, agents solve a distributed multiple hypothesis testing problem by performing two operations at each instant: first, agents incorporate inf ...

The adaptive social learning paradigm helps model how networked agents are able to form opinions on a state of nature and track its drifts in a changing environment. In this framework, the agents repeatedly update their beliefs based on private observation ...

In this paper, we introduce a new class of potential fields, i.e., meta navigation functions (MNFs) to coordinate multi-agent systems. Thanks to the MNF formulation, agents can contribute to each other's coordination via partial and/or total associations, ...

We consider the problem of making a multi-agent system (MAS) resilient to Byzantine failures through replication. We consider a very general model of MAS, where randomness can be involved in the behavior of each agent. We propose the first universal scheme ...

A plethora of real world problems consist of a number of agents that interact, learn, cooperate, coordinate, and compete with others in ever more complex environments. Examples include autonomous vehicles, robotic agents, intelligent infrastructure, IoT de ...

Vision-based drone swarms have recently emerged as a promising alternative to address the fault-tolerance and flexibility limitations of centralized and communication-based aerial collective systems. Although most vision-based control algorithms rely on th ...

The importance of glycans in biological processes are matched by their structural complexity. Coating the surface of most living cells, glycans play key roles in many biological processes, and the role they play is closely related to their structures. Stru ...

The last decades have been punctuated by the development of revolutionary analytical technologies that have enabled the analysis of biomolecular structures and unraveled the roles they play in biological systems. However, certain classes of biomolecules re ...

Consensusability of multi-agent systems (MASs) certifies the existence of a distributed controller capable of driving the states of each subsystem to a consensus value. We study the consensusability of linear interconnected MASs (LIMASs) where, as in sever ...

Given the biological relevance and intrinsic structural complexity of glycans, increasing efforts are being directed towards developing a general glycan database that includes information from different analytical methods. As recently demonstrated, cryogen ...

Adaptation and learning over multi-agent networks is a topic of great relevance with important implications. Elaborating on previous works on single-task networks engaged in decision problems, here we consider the multi-task version in the challenging scen ...

Federated learning has emerged as an umbrella term for centralized coordination strategies in multi-agent environments. While many federated learning architectures process data in an online manner, and are hence adaptive by nature, most performance analyse ...

This work presents and studies a distributed algorithm for solving optimization problems over networks where agents have individual costs to minimize subject to subspace constraints that require the minimizers across the network to lie in a low-dimensional ...

First O-Glycosylation from Unprotected 1-Thioimidoyl Hexofuranosides Assisted by Divalent Cations

Chat with Graph Search

Stochastic pairwise preference convergence in Bayesian agents

Direct observation of glycans bonded to proteins and lipids at the single-molecule level

Combining ion mobility spectrometry and cryogenic ion spectroscopy with enzymatic digestion/synthesis for the study of N-linked glycans

Multi-agent Learning with Privacy Guarantees

Networked Signal and Information Processing: Learning by multiagent systems

Multi-agent actor-critic with time dynamical opponent model

Impact of Redundancy on Resilience in Distributed Optimization and Learning

Partial Information Sharing Over Social Learning Networks

Discovering Influencers in Opinion Formation Over Social Graphs

Meta Navigation Functions: Adaptive Associations for Coordination of Multi-Agent Systems

Byzantine-Resilient Multi-Agent System

Scalable Multi-agent Coordination and Resource Sharing

On the Scalability of Vision-based Drone Swarms in the Presence of Occlusions

Combining cryognic ion spectroscopy with ion mobility for the study of glycan fragmentation

A gas phase approach for glycan analysis: Combining ultrahigh-resolution ion mobility spectrometry with cryogenic vibrational spectroscopy

On Consensusability of Linear Interconnected Multi-Agent Systems and Simultaneous Stabilization

Combining Cryogenic Infrared Spectroscopy with Selective Enzymatic Cleavage for Determining Glycan Primary Structure

Adaptation And Learning In Multi-Task Decision Systems

Dynamic Federated Learning

Distributed Learning over Networks under Subspace Constraints